oops files in wrong spot

Author: SamSaffron

lib/ai_moderation/entry_point.rb

@@ -2,213 +2,16 @@
 
 module DiscourseAi
   module AiModeration
-    class SpamScanner
-      POSTS_TO_SCAN = 3
-      MINIMUM_EDIT_DIFFERENCE = 10
-      EDIT_DELAY_MINUTES = 10
-
-      def self.new_post(post)
-        return if !enabled?
-        return if !should_scan_post?(post)
-
-        Jobs.enqueue(:ai_spam_scan, post_id: post.id)
-      end
-
-      def self.edited_post(post)
-        return if !enabled?
-        return if !should_scan_post?(post)
-        return if scanned_max_times?(post)
-
-        previous_version = post.revisions.last&.modifications&.dig("raw", 0)
-        current_version = post.raw
-
-        # Skip if we can't determine the difference or if change is too small
-        return if !significant_change?(previous_version, current_version)
-
-        last_scan = AiSpamLog.where(post_id: post.id).order(created_at: :desc).first
-
-        if last_scan && last_scan.created_at > EDIT_DELAY_MINUTES.minutes.ago
-          # Schedule delayed job if too soon after last scan
-          delay_minutes =
-            ((last_scan.created_at + EDIT_DELAY_MINUTES.minutes) - Time.current).to_i / 60
-          Jobs.enqueue_in(delay_minutes.minutes, :ai_spam_scan, post_id: post.id)
-        else
-          Jobs.enqueue(:ai_spam_scan, post_id: post.id)
+    class EntryPoint
+      def inject_into(plugin)
+        plugin.on(:post_created) do |post|
+          SpamScanner.new_post(post)
         end
-      end
-
-      def self.enabled?
-        SiteSetting.ai_spam_detection_enabled && SiteSetting.discourse_ai_enabled
-      end
-
-      def self.should_scan_post?(post)
-        return false if !post.present?
-        return false if post.user.trust_level > TrustLevel[1]
-        return false if post.user.post_count > POSTS_TO_SCAN
-        return false if post.topic.private_message?
-        true
-      end
-
-      def self.scanned_max_times?(post)
-        AiSpamLog.where(post_id: post.id).sum(:scan_count) >= 3
-      end
 
-      def self.significant_change?(previous_version, current_version)
-        return true if previous_version.nil? # First edit should be scanned
-
-        # Use Discourse's built-in levenshtein implementation
-        distance =
-          ScreenedEmail.levenshtein(previous_version.to_s[0...1000], current_version.to_s[0...1000])
-
-        distance >= MINIMUM_EDIT_DIFFERENCE
-      end
-
-      def self.perform_scan(post)
-        return if !enabled?
-        return if !should_scan_post?(post)
-
-        settings = AiModerationSetting.spam
-        return if !settings || !settings.llm_model
-
-        llm = settings.llm_model.to_llm
-        custom_instructions = settings.custom_instructions.presence
-
-        system_prompt = build_system_prompt(custom_instructions)
-        prompt = DiscourseAi::Completions::Prompt.new(system_prompt)
-
-        context = build_context(post)
-        prompt.push(type: :user, content: context)
-
-        begin
-          result =
-            llm.generate(
-              prompt,
-              temperature: 0.1,
-              max_tokens: 100,
-              user: Discourse.system_user,
-              feature_name: "spam_detection",
-              feature_context: {
-                post_id: post.id,
-              },
-            )&.strip
-
-          is_spam = result.present? && result.downcase.include?("spam")
-
-          create_log_entry(post, settings.llm_model, result, is_spam)
-
-          handle_spam(post, result) if is_spam
-        rescue StandardError => e
-          Rails.logger.error("Error in SpamScanner for post #{post.id}: #{e.message}")
+        plugin.on(:post_edited) do |post|
+          SpamScanner.edited_post(post)
         end
       end
-
-      private
-
-      def self.build_context(post)
-        context = []
-
-        # Clear distinction between reply and new topic
-        if post.is_first_post?
-          context << "NEW TOPIC POST ANALYSIS"
-          context << "- Topic title: #{post.topic.title}"
-          context << "- Category: #{post.topic.category&.name}"
-        else
-          context << "REPLY POST ANALYSIS"
-          context << "- In topic: #{post.topic.title}"
-          context << "- Topic started by: #{post.topic.user.username}"
-
-          # Include parent post context for replies
-          if post.reply_to_post.present?
-            parent = post.reply_to_post
-            context << "\nReplying to #{parent.user.username}'s post:"
-            context << "#{parent.raw[0..500]}..." if parent.raw.length > 500
-            context << parent.raw if parent.raw.length <= 500
-          end
-        end
-
-        context << "\nPost Author Information:"
-        context << "- Username: #{post.user.username}"
-        context << "- Account age: #{(Time.current - post.user.created_at).to_i / 86_400} days"
-        context << "- Total posts: #{post.user.post_count}"
-        context << "- Trust level: #{post.user.trust_level}"
-
-        context << "\nPost Content:"
-        context << post.raw
-
-        if post.linked_urls.present?
-          context << "\nLinks in post:"
-          context << post.linked_urls.join(", ")
-        end
-
-        context.join("\n")
-      end
-
-      def self.build_system_prompt(custom_instructions)
-        base_prompt = <<~PROMPT
-          You are a spam detection system. Analyze the following post content and context.
-          Respond with "SPAM" if the post is spam, or "NOT_SPAM" if it's legitimate.
-
-          Consider the post type carefully:
-          - For REPLY posts: Check if the response is relevant and topical to the thread
-          - For NEW TOPIC posts: Check if it's a legitimate topic or spam promotion
-
-          A post is spam if it matches any of these criteria:
-          - Contains unsolicited commercial content or promotions
-          - Has suspicious or unrelated external links
-          - Shows patterns of automated/bot posting
-          - Contains irrelevant content or advertisements
-          - For replies: Completely unrelated to the discussion thread
-          - Uses excessive keywords or repetitive text patterns
-          - Shows suspicious formatting or character usage
-
-          Be especially strict with:
-          - Replies that ignore the previous conversation
-          - Posts containing multiple unrelated external links
-          - Generic responses that could be posted anywhere
-
-          Be fair to:
-          - New users making legitimate first contributions
-          - Non-native speakers making genuine efforts to participate
-          - Topic-relevant product mentions in appropriate contexts
-        PROMPT
-
-        if custom_instructions.present?
-          base_prompt += "\n\nAdditional site-specific instructions:\n#{custom_instructions}"
-        end
-
-        base_prompt
-      end
-
-      def self.create_log_entry(post, llm_model, result, is_spam)
-        log = AiSpamLog.find_or_initialize_by(post_id: post.id)
-
-        if log.new_record?
-          log.llm_model = llm_model
-          log.is_spam = is_spam
-          log.scan_count = 1
-        else
-          log.scan_count += 1
-        end
-
-        last_audit = DiscourseAi::ApiAuditLog.last
-        log.last_ai_api_audit_log_id = last_audit.id if last_audit
-
-        log.save!
-      end
-
-      def self.handle_spam(post, result)
-        SpamRule::AutoSilence.new(post.user, post).silence_user
-
-        reason = I18n.t("discourse_ai.spam_detection.flag_reason", result: result)
-
-        PostActionCreator.new(
-          Discourse.system_user,
-          post,
-          PostActionType.types[:spam],
-          message: reason,
-          queue_for_review: true,
-        ).perform
-      end
     end
   end
 end