FIX: Process succesfully generated embeddings even if some failed (#1500)

lib/embeddings/vector.rb

@@ -42,13 +42,14 @@ module DiscourseAi
                 .then_on(pool) do |w_prepared_text|
                   w_prepared_text.merge(embedding: embedding_gen.perform!(w_prepared_text[:text]))
                 end
+                .rescue { nil } # We log the error during #perform. Skip failed embeddings.
             end
             .compact
 
         Concurrent::Promises
           .zip(*promised_embeddings)
           .value!
-          .each { |e| schema.store(e[:target], e[:embedding], e[:digest]) }
+          .each { |e| schema.store(e[:target], e[:embedding], e[:digest]) if e.present? }
       ensure
         pool.shutdown
         pool.wait_for_termination

lib/inference/cloudflare_workers_ai.rb

@@ -26,8 +26,6 @@ module ::DiscourseAi
         case response.status
         when 200
           JSON.parse(response.body, symbolize_names: true).dig(:result, :data).first
-        when 429
-          # TODO add a AdminDashboard Problem?
         else
           Rails.logger.warn(
             "Cloudflare Workers AI Embeddings failed with status: #{response.status} body: #{response.body}",

lib/inference/gemini_embeddings.rb

@@ -22,8 +22,6 @@ module ::DiscourseAi
         case response.status
         when 200
           JSON.parse(response.body, symbolize_names: true).dig(:embedding, :values)
-        when 429
-          # TODO add a AdminDashboard Problem?
         else
           Rails.logger.warn(
             "Google Gemini Embeddings failed with status: #{response.status} body: #{response.body}",

lib/inference/open_ai_embeddings.rb

@@ -30,8 +30,6 @@ module ::DiscourseAi
         case response.status
         when 200
           JSON.parse(response.body, symbolize_names: true).dig(:data, 0, :embedding)
-        when 429
-          # TODO add a AdminDashboard Problem?
         else
           Rails.logger.warn(
             "OpenAI Embeddings failed with status: #{response.status} body: #{response.body}",

spec/lib/inference/cloudflare_workers_ai_spec.rb

@@ -40,16 +40,7 @@ RSpec.describe DiscourseAi::Inference::CloudflareWorkersAi do
       end
     end
 
-    context "when the response status is 429" do
+    context "when the response status is not 200" do
-      let(:response_status) { 429 }
-      let(:response_body) { "" }
-
-      it "doesn't raises a Net::HTTPBadResponse error" do
-        expect { subject.perform!(content) }.not_to raise_error
-      end
-    end
-
-    context "when the response status is not 200 or 429" do
       let(:response_status) { 500 }
       let(:response_body) { "Internal Server Error" }
 

spec/lib/modules/embeddings/vector_spec.rb

@@ -83,17 +83,34 @@ RSpec.describe DiscourseAi::Embeddings::Vector do
 
         expect(topics_schema.find_by_target(topic).updated_at).to eq_time(original_vector_gen)
       end
+
+      context "when one of the concurrently generated embeddings fails" do
+        it "still processes the succesful ones" do
+          text = vdef.prepare_target_text(topic)
+
+          text2 = vdef.prepare_target_text(topic_2)
+
+          stub_vector_mapping(text, expected_embedding_1)
+          stub_vector_mapping(text2, expected_embedding_2, result_status: 429)
+
+          vector.gen_bulk_reprensentations(Topic.where(id: [topic.id, topic_2.id]))
+
+          expect(topics_schema.find_by_embedding(expected_embedding_1).topic_id).to eq(topic.id)
+          expect(topics_schema.find_by_target(topic_2)).to be_nil
+        end
+      end
     end
   end
 
   context "with open_ai as the provider" do
     fab!(:vdef) { Fabricate(:open_ai_embedding_def) }
 
-    def stub_vector_mapping(text, expected_embedding)
+    def stub_vector_mapping(text, expected_embedding, result_status: 200)
       EmbeddingsGenerationStubs.openai_service(
         vdef.lookup_custom_param("model_name"),
         text,
         expected_embedding,
+        result_status: result_status,
       )
     end
 
@@ -123,8 +140,12 @@ RSpec.describe DiscourseAi::Embeddings::Vector do
   context "with hugging_face as the provider" do
     fab!(:vdef) { Fabricate(:embedding_definition) }
 
-    def stub_vector_mapping(text, expected_embedding)
+    def stub_vector_mapping(text, expected_embedding, result_status: 200)
-      EmbeddingsGenerationStubs.hugging_face_service(text, expected_embedding)
+      EmbeddingsGenerationStubs.hugging_face_service(
+        text,
+        expected_embedding,
+        result_status: result_status,
+      )
     end
 
     it_behaves_like "generates and store embeddings using a vector definition"
@@ -133,8 +154,13 @@ RSpec.describe DiscourseAi::Embeddings::Vector do
   context "with google as the provider" do
     fab!(:vdef) { Fabricate(:gemini_embedding_def) }
 
-    def stub_vector_mapping(text, expected_embedding)
+    def stub_vector_mapping(text, expected_embedding, result_status: 200)
-      EmbeddingsGenerationStubs.gemini_service(vdef.api_key, text, expected_embedding)
+      EmbeddingsGenerationStubs.gemini_service(
+        vdef.api_key,
+        text,
+        expected_embedding,
+        result_status: result_status,
+      )
     end
 
     it_behaves_like "generates and store embeddings using a vector definition"
@@ -143,8 +169,12 @@ RSpec.describe DiscourseAi::Embeddings::Vector do
   context "with cloudflare as the provider" do
     fab!(:vdef) { Fabricate(:cloudflare_embedding_def) }
 
-    def stub_vector_mapping(text, expected_embedding)
+    def stub_vector_mapping(text, expected_embedding, result_status: 200)
-      EmbeddingsGenerationStubs.cloudflare_service(text, expected_embedding)
+      EmbeddingsGenerationStubs.cloudflare_service(
+        text,
+        expected_embedding,
+        result_status: result_status,
+      )
     end
 
     it_behaves_like "generates and store embeddings using a vector definition"

spec/support/embeddings_generation_stubs.rb

@@ -2,35 +2,35 @@
 
 class EmbeddingsGenerationStubs
   class << self
-    def hugging_face_service(string, embedding)
+    def hugging_face_service(string, embedding, result_status: 200)
       WebMock
         .stub_request(:post, "https://test.com/embeddings")
         .with(body: JSON.dump({ inputs: string, truncate: true }))
-        .to_return(status: 200, body: JSON.dump([embedding]))
+        .to_return(status: result_status, body: JSON.dump([embedding]))
     end
 
-    def openai_service(model, string, embedding, extra_args: {})
+    def openai_service(model, string, embedding, result_status: 200, extra_args: {})
       WebMock
         .stub_request(:post, "https://api.openai.com/v1/embeddings")
         .with(body: JSON.dump({ model: model, input: string }.merge(extra_args)))
-        .to_return(status: 200, body: JSON.dump({ data: [{ embedding: embedding }] }))
+        .to_return(status: result_status, body: JSON.dump({ data: [{ embedding: embedding }] }))
     end
 
-    def gemini_service(api_key, string, embedding)
+    def gemini_service(api_key, string, embedding, result_status: 200)
       WebMock
         .stub_request(
           :post,
           "https://generativelanguage.googleapis.com/v1beta/models/embedding-001:embedContent\?key\=#{api_key}",
         )
         .with(body: JSON.dump({ content: { parts: [{ text: string }] } }))
-        .to_return(status: 200, body: JSON.dump({ embedding: { values: embedding } }))
+        .to_return(status: result_status, body: JSON.dump({ embedding: { values: embedding } }))
     end
 
-    def cloudflare_service(string, embedding)
+    def cloudflare_service(string, embedding, result_status: 200)
       WebMock
         .stub_request(:post, "https://test.com/embeddings")
         .with(body: JSON.dump({ text: [string] }))
-        .to_return(status: 200, body: JSON.dump({ result: { data: [embedding] } }))
+        .to_return(status: result_status, body: JSON.dump({ result: { data: [embedding] } }))
     end
   end
 end