Add AI tag model and UI.

Add a database model for storing AI-predicted tags, and add a UI for browsing and searching these tags.

AI tags are generated by the Danbooru Autotagger (https://github.com/danbooru/autotagger). See that
repo for details about the model.

The database schema is `ai_tags (media_asset_id integer, tag_id integer, score smallint)`. This is
designed to be as space-efficient as possible, since in production we have over 300 million
AI-generated tags (6 million images and 50 tags per post). This amounts to over 10GB in size, plus
indexes.

You can search for AI tags using e.g. `ai:scenery`. You can do `ai:scenery -scenery` to find posts
where the scenery tag is potentially missing, or `scenery -ai:scenery` to find posts that are
potentially mistagged (or more likely where the AI missed the tag).

You can browse AI tags at https://danbooru.donmai.us/ai_tags. On this page you can filter by
confidence level. You can also search unposted media assets by AI tag.

To generate tags, use the `autotag` script from the Autotagger repo, something like this:

  docker run --rm -v ~/danbooru/public/data/360x360:/images ghcr.io/danbooru/autotagger ./autotag -c -f /images | gzip > tags.csv.gz

To import tags, use the fix script in script/fixes/. Expect a Danbooru-size dataset to take
hours to days to generate tags, then 20-30 minutes to import. Currently this all has to be done by hand.

app/controllers/ai_tags_controller.rb

@@ -0,0 +1,15 @@
+# frozen_string_literal: true
+
+class AITagsController < ApplicationController
+  respond_to :js, :html, :json, :xml
+
+  def index
+    @ai_tags = authorize AITag.visible(CurrentUser.user).paginated_search(params, count_pages: false)
+    @ai_tags = @ai_tags.includes(:media_asset, :tag, :post) if request.format.html?
+
+    @mode = params.fetch(:mode, "gallery")
+    @preview_size = params[:size].presence || cookies[:post_preview_size].presence || MediaAssetGalleryComponent::DEFAULT_SIZE
+
+    respond_with(@ai_tags)
+  end
+end