FIX: ensure we only attempt embedding once every 15 minutes (#76)

This also heavily reduced log noise and ensures our exception handling is
more surgical.

lib/modules/embeddings/semantic_related.rb

@@ -3,6 +3,19 @@
 module DiscourseAi
   module Embeddings
     class SemanticRelated
+      def self.semantic_suggested_key(topic_id)
+        "semantic-suggested-topic-#{topic_id}"
+      end
+
+      def self.build_semantic_suggested_key(topic_id)
+        "build-semantic-suggested-topic-#{topic_id}"
+      end
+
+      def self.clear_cache_for(topic)
+        Discourse.cache.delete(semantic_suggested_key(topic.id))
+        Discourse.redis.del(build_semantic_suggested_key(topic.id))
+      end
+
       def self.candidates_for(topic)
         return ::Topic.none if SiteSetting.ai_embeddings_semantic_related_topics < 1
 
@@ -25,12 +38,19 @@ module DiscourseAi
           candidate_ids =
             Discourse
               .cache
-              .fetch("semantic-suggested-topic-#{topic.id}", expires_in: cache_for) do
+              .fetch(semantic_suggested_key(topic.id), expires_in: cache_for) do
                 DiscourseAi::Embeddings::Topic.new.symmetric_semantic_search(model, topic)
               end
-        rescue StandardError => e
-          Rails.logger.error("SemanticRelated: #{e}")
-          Jobs.enqueue(:generate_embeddings, topic_id: topic.id)
+        rescue MissingEmbeddingError
+          # avoid a flood of jobs when visiting topic
+          if Discourse.redis.set(
+               build_semantic_suggested_key(topic.id),
+               "queued",
+               ex: 15.minutes.to_i,
+               nx: true,
+             )
+            Jobs.enqueue(:generate_embeddings, topic_id: topic.id)
+          end
           return ::Topic.none
         end
 

lib/modules/embeddings/topic.rb

@@ -2,6 +2,8 @@
 
 module DiscourseAi
   module Embeddings
+    MissingEmbeddingError = Class.new(StandardError)
+
     class Topic
       def generate_and_store_embeddings_for(topic)
         return unless SiteSetting.ai_embeddings_enabled
@@ -17,29 +19,12 @@ module DiscourseAi
       end
 
       def symmetric_semantic_search(model, topic)
-        candidate_ids =
-          DiscourseAi::Database::Connection.db.query(<<~SQL, topic_id: topic.id).map(&:topic_id)
-          SELECT
-            topic_id
-          FROM
-            topic_embeddings_#{model.name.underscore}
-          ORDER BY
-            embedding #{model.pg_function} (
-              SELECT
-                embedding
-              FROM
-                topic_embeddings_#{model.name.underscore}
-              WHERE
-                topic_id = :topic_id
-              LIMIT 1
-            )
-          LIMIT 100
-        SQL
+        candidate_ids = query_symmetric_embeddings(model, topic)
 
         # Happens when the topic doesn't have any embeddings
         # I'd rather not use Exceptions to control the flow, so this should be refactored soon
         if candidate_ids.empty? || !candidate_ids.include?(topic.id)
-          raise StandardError, "No embeddings found for topic #{topic.id}"
+          raise MissingEmbeddingError, "No embeddings found for topic #{topic.id}"
         end
 
         candidate_ids
@@ -70,6 +55,26 @@ module DiscourseAi
 
       private
 
+      def query_symmetric_embeddings(model, topic)
+        DiscourseAi::Database::Connection.db.query(<<~SQL, topic_id: topic.id).map(&:topic_id)
+          SELECT
+            topic_id
+          FROM
+            topic_embeddings_#{model.name.underscore}
+          ORDER BY
+            embedding #{model.pg_function} (
+              SELECT
+                embedding
+              FROM
+                topic_embeddings_#{model.name.underscore}
+              WHERE
+                topic_id = :topic_id
+              LIMIT 1
+            )
+          LIMIT 100
+        SQL
+      end
+
       def persist_embedding(topic, model, embedding)
         DiscourseAi::Database::Connection.db.exec(<<~SQL, topic_id: topic.id, embedding: embedding)
             INSERT INTO topic_embeddings_#{model.name.underscore} (topic_id, embedding)

spec/lib/modules/embeddings/semantic_related_spec.rb

@@ -16,33 +16,65 @@ describe DiscourseAi::Embeddings::SemanticRelated do
   before { SiteSetting.ai_embeddings_semantic_related_topics_enabled = true }
 
   describe "#candidates_for" do
-    before do
-      Discourse.cache.clear
-      DiscourseAi::Embeddings::Topic
-        .any_instance
-        .expects(:symmetric_semantic_search)
-        .returns(Topic.unscoped.order(id: :desc).limit(100).pluck(:id))
+    context "when embeddings do not exist" do
+      let (:topic) do
+        topic = Fabricate(:topic)
+        described_class.clear_cache_for(target)
+        topic
+      end
+
+      it "queues job only once per 15 minutes" do
+        # sadly we need to mock a DB connection to return nothing
+        DiscourseAi::Embeddings::Topic
+          .any_instance
+          .expects(:query_symmetric_embeddings)
+          .returns([])
+          .twice
+
+        results = nil
+
+        expect_enqueued_with(job: :generate_embeddings, args: { topic_id: topic.id }) do
+          results = described_class.candidates_for(topic).to_a
+        end
+
+        expect(results).to eq([])
+
+        expect_not_enqueued_with(job: :generate_embeddings, args: { topic_id: topic.id }) do
+          results = described_class.candidates_for(topic).to_a
+        end
+
+        expect(results).to eq([])
+      end
     end
+    context "when embeddings exist" do
+      before do
+        Discourse.cache.clear
+        DiscourseAi::Embeddings::Topic
+          .any_instance
+          .expects(:symmetric_semantic_search)
+          .returns(Topic.unscoped.order(id: :desc).limit(100).pluck(:id))
+      end
 
-    after { Discourse.cache.clear }
+      after { Discourse.cache.clear }
 
-    it "returns the related topics without non public topics" do
-      results = described_class.candidates_for(target).to_a
-      expect(results).to include(normal_topic_1)
-      expect(results).to include(normal_topic_2)
-      expect(results).to include(normal_topic_3)
-      expect(results).to include(closed_topic)
-      expect(results).to_not include(target)
-      expect(results).to_not include(unlisted_topic)
-      expect(results).to_not include(private_topic)
-      expect(results).to_not include(secured_category_topic)
-    end
-
-    context "when ai_embeddings_semantic_related_include_closed_topics is false" do
-      before { SiteSetting.ai_embeddings_semantic_related_include_closed_topics = false }
-      it "do not return closed topics" do
+      it "returns the related topics without non public topics" do
         results = described_class.candidates_for(target).to_a
-        expect(results).to_not include(closed_topic)
+        expect(results).to include(normal_topic_1)
+        expect(results).to include(normal_topic_2)
+        expect(results).to include(normal_topic_3)
+        expect(results).to include(closed_topic)
+        expect(results).to_not include(target)
+        expect(results).to_not include(unlisted_topic)
+        expect(results).to_not include(private_topic)
+        expect(results).to_not include(secured_category_topic)
+      end
+
+      context "when ai_embeddings_semantic_related_include_closed_topics is false" do
+        before { SiteSetting.ai_embeddings_semantic_related_include_closed_topics = false }
+        it "do not return closed topics" do
+          results = described_class.candidates_for(target).to_a
+          expect(results).to_not include(closed_topic)
+        end
       end
     end
   end