FIX: Fix embeddings truncation strategy

lib/modules/embeddings/strategies/truncation.rb

@@ -22,17 +22,17 @@ def initialize(target, model)
           @model = model
           @target = target
           @tokenizer = @model.tokenizer
-          @max_length = @model.max_sequence_length
-          @processed_target = +""
+          @max_length = @model.max_sequence_length - 2
+          @processed_target = nil
         end
 
         # Need a better name for this method
         def process!
           case @target
           when Topic
-            topic_truncation(@target)
+            @processed_target = topic_truncation(@target)
           when Post
-            post_truncation(@target)
+            @processed_target = post_truncation(@target)
           else
             raise ArgumentError, "Invalid target type"
           end
@@ -41,7 +41,7 @@ def process!
         end
 
         def topic_truncation(topic)
-          t = @processed_target
+          t = +""
 
           t << topic.title
           t << "\n\n"
@@ -54,15 +54,15 @@ def topic_truncation(topic)
 
           topic.posts.find_each do |post|
             t << post.raw
-            break if @tokenizer.size(t) >= @max_length
+            break if @tokenizer.size(t) >= @max_length #maybe keep a partial counter to speed this up?
             t << "\n\n"
           end
 
           @tokenizer.truncate(t, @max_length)
         end
 
         def post_truncation(post)
-          t = processed_target
+          t = +""
 
           t << post.topic.title
           t << "\n\n"

spec/lib/modules/embeddings/strategies/truncation_spec.rb

@@ -0,0 +1,31 @@
+# frozen_string_literal: true
+
+RSpec.describe DiscourseAi::Embeddings::Strategies::Truncation do
+  describe "#process!" do
+    context "when the model uses OpenAI to create embeddings" do
+      before { SiteSetting.max_post_length = 100_000 }
+
+      fab!(:topic) { Fabricate(:topic) }
+      fab!(:post) do
+        Fabricate(:post, topic: topic, raw: "Baby, bird, bird, bird\nBird is the word\n" * 500)
+      end
+      fab!(:post) do
+        Fabricate(
+          :post,
+          topic: topic,
+          raw: "Don't you know about the bird?\nEverybody knows that the bird is a word\n" * 400,
+        )
+      end
+      fab!(:post) { Fabricate(:post, topic: topic, raw: "Surfin' bird\n" * 800) }
+
+      let(:model) { DiscourseAi::Embeddings::Models::Base.descendants.sample(1).first }
+      let(:truncation) { described_class.new(topic, model) }
+
+      it "truncates a topic" do
+        truncation.process!
+
+        expect(model.tokenizer.size(truncation.processed_target)).to be <= model.max_sequence_length
+      end
+    end
+  end
+end