Revert "UX: Validate embeddings settings (#455)" (#456)

This reverts commit 85fca89e01.

config/locales/server.en.yml

@@ -251,12 +251,3 @@ en:
         configuration_hint:
           one: "Make sure the `%{settings}` setting was configured."
           other: "Make sure these settings were configured: %{settings}"
-
-    embeddings:
-      configuration:
-        disable_embeddings: "You have to disable 'ai embeddings enabled' first."
-        choose_model: "Set 'ai embeddings model' first."
-        model_unreachable: "We failed to generate a test embedding with this model. Check your settings are correct."
-        hint: 
-          one: "Make sure the `%{settings}` setting was configured."
-          other: "Make sure the settings of the provider you want were configured. Options are: %{settings}"

config/settings.yml

@@ -216,7 +216,6 @@ discourse_ai:
   ai_embeddings_enabled:
     default: false
     client: true
-    validator: "DiscourseAi::Configuration::EmbeddingsDependencyValidator"
   ai_embeddings_discourse_service_api_endpoint: ""
   ai_embeddings_discourse_service_api_endpoint_srv:
     default: ""
@@ -226,10 +225,17 @@ discourse_ai:
     secret: true
   ai_embeddings_model:
     type: enum
-    default: ""
+    list_type: compact
+    default: "bge-large-en"
     allow_any: false
-    enum: "DiscourseAi::Configuration::EmbeddingsModelEnumerator"
+    choices:
-    validator: "DiscourseAi::Configuration::EmbeddingsModelValidator"
+      - all-mpnet-base-v2
+      - text-embedding-ada-002
+      - text-embedding-3-small
+      - text-embedding-3-large
+      - multilingual-e5-large
+      - bge-large-en
+      - gemini
   ai_embeddings_per_post_enabled:
     default: false
     hidden: true

lib/configuration/embeddings_dependency_validator.rb

@@ -1,21 +0,0 @@
-# frozen_string_literal: true
-
-module DiscourseAi
-  module Configuration
-    class EmbeddingsDependencyValidator
-      def initialize(opts = {})
-        @opts = opts
-      end
-
-      def valid_value?(val)
-        return true if val == "f"
-
-        SiteSetting.ai_embeddings_model.present?
-      end
-
-      def error_message
-        I18n.t("discourse_ai.embeddings.configuration.choose_model")
-      end
-    end
-  end
-end

lib/configuration/embeddings_model_enumerator.rb

@@ -1,25 +0,0 @@
-# frozen_string_literal: true
-
-require "enum_site_setting"
-
-module DiscourseAi
-  module Configuration
-    class EmbeddingsModelEnumerator < ::EnumSiteSetting
-      def self.valid_value?(val)
-        true
-      end
-
-      def self.values
-        %w[
-          all-mpnet-base-v2
-          text-embedding-ada-002
-          text-embedding-3-small
-          text-embedding-3-large
-          multilingual-e5-large
-          bge-large-en
-          gemini
-        ]
-      end
-    end
-  end
-end

lib/configuration/embeddings_model_validator.rb

@@ -1,56 +0,0 @@
-# frozen_string_literal: true
-
-module DiscourseAi
-  module Configuration
-    class EmbeddingsModelValidator
-      def initialize(opts = {})
-        @opts = opts
-      end
-
-      def valid_value?(val)
-        if val == ""
-          @embeddings_enabled = SiteSetting.ai_embeddings_enabled
-          return !@embeddings_enabled
-        end
-
-        representation =
-          DiscourseAi::Embeddings::VectorRepresentations::Base.find_representation(val)
-
-        return false if representation.nil?
-
-        # Skip config for tests. We stub embeddings generation anyway.
-        return true if Rails.env.test? && val
-
-        if !representation.correctly_configured?
-          @representation = representation
-          return false
-        end
-
-        if !can_generate_embeddings?(val)
-          @unreachable = true
-          return false
-        end
-
-        true
-      end
-
-      def error_message
-        if @embeddings_enabled
-          return(I18n.t("discourse_ai.embeddings.configuration.disable_embeddings"))
-        end
-
-        return(I18n.t("discourse_ai.embeddings.configuration.model_unreachable")) if @unreachable
-
-        @representation&.configuration_hint
-      end
-
-      def can_generate_embeddings?(val)
-        DiscourseAi::Embeddings::VectorRepresentations::Base
-          .find_representation(val)
-          .new(DiscourseAi::Embeddings::Strategies::Truncation.new)
-          .vector_from("this is a test")
-          .present?
-      end
-    end
-  end
-end

lib/embeddings/vector_representations/all_mpnet_base_v2.rb

@@ -4,34 +4,19 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class AllMpnetBaseV2 < Base
-        class << self
-          def name
-            "all-mpnet-base-v2"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_embeddings_discourse_service_api_endpoint_srv.present? ||
-              SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
-          end
-
-          def dependant_setting_names
-            %w[
-              ai_embeddings_discourse_service_api_key
-              ai_embeddings_discourse_service_api_endpoint_srv
-              ai_embeddings_discourse_service_api_endpoint
-            ]
-          end
-        end
-
         def vector_from(text)
           DiscourseAi::Inference::DiscourseClassifier.perform!(
             "#{discourse_embeddings_endpoint}/api/v1/classify",
-            self.class.name,
+            name,
             text,
             SiteSetting.ai_embeddings_discourse_service_api_key,
           )
         end
 
+        def name
+          "all-mpnet-base-v2"
+        end
+
         def dimensions
           768
         end

lib/embeddings/vector_representations/base.rb

@@ -4,8 +4,7 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class Base
-        class << self
+        def self.current_representation(strategy)
-          def find_representation(model_name)
           # we are explicit here cause the loader may have not
           # loaded the subclasses yet
           [
@@ -16,29 +15,7 @@ module DiscourseAi
             DiscourseAi::Embeddings::VectorRepresentations::TextEmbeddingAda002,
             DiscourseAi::Embeddings::VectorRepresentations::TextEmbedding3Small,
             DiscourseAi::Embeddings::VectorRepresentations::TextEmbedding3Large,
-            ].find { _1.name == model_name }
+          ].map { _1.new(strategy) }.find { _1.name == SiteSetting.ai_embeddings_model }
-          end
-
-          def current_representation(strategy)
-            find_representation(SiteSetting.ai_embeddings_model).new(strategy)
-          end
-
-          def correctly_configured?
-            raise NotImplementedError
-          end
-
-          def dependant_setting_names
-            raise NotImplementedError
-          end
-
-          def configuration_hint
-            settings = dependant_setting_names
-            I18n.t(
-              "discourse_ai.embeddings.configuration.hint",
-              settings: settings.join(", "),
-              count: settings.length,
-            )
-          end
         end
 
         def initialize(strategy)

lib/embeddings/vector_representations/bge_large_en.rb

@@ -4,32 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class BgeLargeEn < Base
-        class << self
-          def name
-            "bge-large-en"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_cloudflare_workers_api_token.present? ||
-              DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured? ||
-              (
-                SiteSetting.ai_embeddings_discourse_service_api_endpoint_srv.present? ||
-                  SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
-              )
-          end
-
-          def dependant_setting_names
-            %w[
-              ai_cloudflare_workers_api_token
-              ai_hugging_face_tei_endpoint_srv
-              ai_hugging_face_tei_endpoint
-              ai_embeddings_discourse_service_api_key
-              ai_embeddings_discourse_service_api_endpoint_srv
-              ai_embeddings_discourse_service_api_endpoint
-            ]
-          end
-        end
-
         def vector_from(text)
           if SiteSetting.ai_cloudflare_workers_api_token.present?
             DiscourseAi::Inference::CloudflareWorkersAi
@@ -51,6 +25,10 @@ module DiscourseAi
           end
         end
 
+        def name
+          "bge-large-en"
+        end
+
         def inference_model_name
           "baai/bge-large-en-v1.5"
         end

lib/embeddings/vector_representations/gemini.rb

@@ -4,20 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class Gemini < Base
-        class << self
-          def name
-            "gemini"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_gemini_api_key.present?
-          end
-
-          def dependant_setting_names
-            %w[ai_gemini_api_key]
-          end
-        end
-
         def id
           5
         end
@@ -26,6 +12,10 @@ module DiscourseAi
           1
         end
 
+        def name
+          "gemini"
+        end
+
         def dimensions
           768
         end

lib/embeddings/vector_representations/multilingual_e5_large.rb

@@ -4,30 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class MultilingualE5Large < Base
-        class << self
-          def name
-            "multilingual-e5-large"
-          end
-
-          def correctly_configured?
-            DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured? ||
-              (
-                SiteSetting.ai_embeddings_discourse_service_api_endpoint_srv.present? ||
-                  SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
-              )
-          end
-
-          def dependant_setting_names
-            %w[
-              ai_hugging_face_tei_endpoint_srv
-              ai_hugging_face_tei_endpoint
-              ai_embeddings_discourse_service_api_key
-              ai_embeddings_discourse_service_api_endpoint_srv
-              ai_embeddings_discourse_service_api_endpoint
-            ]
-          end
-        end
-
         def vector_from(text)
           if DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured?
             truncated_text = tokenizer.truncate(text, max_sequence_length - 2)
@@ -35,7 +11,7 @@ module DiscourseAi
           elsif discourse_embeddings_endpoint.present?
             DiscourseAi::Inference::DiscourseClassifier.perform!(
               "#{discourse_embeddings_endpoint}/api/v1/classify",
-              self.class.name,
+              name,
               "query: #{text}",
               SiteSetting.ai_embeddings_discourse_service_api_key,
             )
@@ -52,6 +28,10 @@ module DiscourseAi
           1
         end
 
+        def name
+          "multilingual-e5-large"
+        end
+
         def dimensions
           1024
         end

lib/embeddings/vector_representations/text_embedding_3_large.rb

@@ -4,20 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class TextEmbedding3Large < Base
-        class << self
-          def name
-            "text-embedding-3-large"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_openai_api_key.present?
-          end
-
-          def dependant_setting_names
-            %w[ai_openai_api_key]
-          end
-        end
-
         def id
           7
         end
@@ -26,6 +12,10 @@ module DiscourseAi
           1
         end
 
+        def name
+          "text-embedding-3-large"
+        end
+
         def dimensions
           # real dimentions are 3072, but we only support up to 2000 in the
           # indexes, so we downsample to 2000 via API
@@ -48,7 +38,7 @@ module DiscourseAi
           response =
             DiscourseAi::Inference::OpenAiEmbeddings.perform!(
               text,
-              model: self.clas.name,
+              model: name,
               dimensions: dimensions,
             )
           response[:data].first[:embedding]

lib/embeddings/vector_representations/text_embedding_3_small.rb

@@ -4,20 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class TextEmbedding3Small < Base
-        class << self
-          def name
-            "text-embedding-3-small"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_openai_api_key.present?
-          end
-
-          def dependant_setting_names
-            %w[ai_openai_api_key]
-          end
-        end
-
         def id
           6
         end
@@ -26,6 +12,10 @@ module DiscourseAi
           1
         end
 
+        def name
+          "text-embedding-3-small"
+        end
+
         def dimensions
           1536
         end
@@ -43,7 +33,7 @@ module DiscourseAi
         end
 
         def vector_from(text)
-          response = DiscourseAi::Inference::OpenAiEmbeddings.perform!(text, model: self.class.name)
+          response = DiscourseAi::Inference::OpenAiEmbeddings.perform!(text, model: name)
           response[:data].first[:embedding]
         end
 

lib/embeddings/vector_representations/text_embedding_ada_002.rb

@@ -4,20 +4,6 @@ module DiscourseAi
   module Embeddings
     module VectorRepresentations
       class TextEmbeddingAda002 < Base
-        class << self
-          def name
-            "text-embedding-ada-002"
-          end
-
-          def correctly_configured?
-            SiteSetting.ai_openai_api_key.present?
-          end
-
-          def dependant_setting_names
-            %w[ai_openai_api_key]
-          end
-        end
-
         def id
           2
         end
@@ -26,6 +12,10 @@ module DiscourseAi
           1
         end
 
+        def name
+          "text-embedding-ada-002"
+        end
+
         def dimensions
           1536
         end
@@ -43,7 +33,7 @@ module DiscourseAi
         end
 
         def vector_from(text)
-          response = DiscourseAi::Inference::OpenAiEmbeddings.perform!(text, model: self.class.name)
+          response = DiscourseAi::Inference::OpenAiEmbeddings.perform!(text, model: name)
           response[:data].first[:embedding]
         end
 

spec/jobs/scheduled/embeddings_backfill_spec.rb

@@ -25,7 +25,6 @@ RSpec.describe Jobs::EmbeddingsBackfill do
   end
 
   it "backfills topics based on bumped_at date" do
-    SiteSetting.ai_embeddings_model = "bge-large-en"
     SiteSetting.ai_embeddings_enabled = true
     SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
     SiteSetting.ai_embeddings_backfill_batch_size = 1

spec/lib/modules/ai_bot/tools/search_spec.rb

@@ -70,7 +70,6 @@ RSpec.describe DiscourseAi::AiBot::Tools::Search do
         SiteSetting.ai_embeddings_semantic_search_hyde_model = "fake:fake"
         SiteSetting.ai_embeddings_semantic_search_enabled = true
         SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
-        SiteSetting.ai_embeddings_model = "bge-large-en"
 
         hyde_embedding = [0.049382, 0.9999]
         EmbeddingsGenerationStubs.discourse_service(

spec/lib/modules/embeddings/entry_point_spec.rb

@@ -13,8 +13,6 @@ describe DiscourseAi::Embeddings::EntryPoint do
         )
       end
 
-      before { SiteSetting.ai_embeddings_model = "bge-large-en" }
-
       it "queues a job on create if embeddings is enabled" do
         SiteSetting.ai_embeddings_enabled = true
 

spec/lib/modules/embeddings/jobs/generate_embeddings_spec.rb

@@ -6,8 +6,8 @@ RSpec.describe Jobs::GenerateEmbeddings do
   describe "#execute" do
     before do
       SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
-      SiteSetting.ai_embeddings_model = "bge-large-en"
       SiteSetting.ai_embeddings_enabled = true
+      SiteSetting.ai_embeddings_model = "bge-large-en"
     end
 
     fab!(:topic) { Fabricate(:topic) }
@@ -27,7 +27,7 @@ RSpec.describe Jobs::GenerateEmbeddings do
           vector_rep.tokenizer,
           vector_rep.max_sequence_length - 2,
         )
-      EmbeddingsGenerationStubs.discourse_service(vector_rep.class.name, text, expected_embedding)
+      EmbeddingsGenerationStubs.discourse_service(vector_rep.name, text, expected_embedding)
 
       job.execute(target_id: topic.id, target_type: "Topic")
 
@@ -39,7 +39,7 @@ RSpec.describe Jobs::GenerateEmbeddings do
 
       text =
         truncation.prepare_text_from(post, vector_rep.tokenizer, vector_rep.max_sequence_length - 2)
-      EmbeddingsGenerationStubs.discourse_service(vector_rep.class.name, text, expected_embedding)
+      EmbeddingsGenerationStubs.discourse_service(vector_rep.name, text, expected_embedding)
 
       job.execute(target_id: post.id, target_type: "Post")
 

spec/lib/modules/embeddings/semantic_related_spec.rb

@@ -13,10 +13,7 @@ describe DiscourseAi::Embeddings::SemanticRelated do
   fab!(:secured_category_topic) { Fabricate(:topic, category: secured_category) }
   fab!(:closed_topic) { Fabricate(:topic, closed: true) }
 
-  before do
+  before { SiteSetting.ai_embeddings_semantic_related_topics_enabled = true }
-    SiteSetting.ai_embeddings_model = "bge-large-en"
-    SiteSetting.ai_embeddings_semantic_related_topics_enabled = true
-  end
 
   describe "#related_topic_ids_for" do
     context "when embeddings do not exist" do

spec/lib/modules/embeddings/semantic_search_spec.rb

@@ -14,7 +14,6 @@ RSpec.describe DiscourseAi::Embeddings::SemanticSearch do
 
     before do
       SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
-      SiteSetting.ai_embeddings_model = "bge-large-en"
 
       hyde_embedding = [0.049382, 0.9999]
       EmbeddingsGenerationStubs.discourse_service(

spec/lib/modules/embeddings/semantic_topic_query_spec.rb

@@ -4,8 +4,6 @@ describe DiscourseAi::Embeddings::EntryPoint do
   fab!(:user) { Fabricate(:user) }
 
   describe "SemanticTopicQuery extension" do
-    before { SiteSetting.ai_embeddings_model = "bge-large-en" }
-
     describe "#list_semantic_related_topics" do
       subject(:topic_query) { DiscourseAi::Embeddings::SemanticTopicQuery.new(user) }
 

spec/lib/modules/embeddings/vector_representations/all_mpnet_base_v2_spec.rb

@@ -10,7 +10,7 @@ RSpec.describe DiscourseAi::Embeddings::VectorRepresentations::AllMpnetBaseV2 do
   before { SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com" }
 
   def stub_vector_mapping(text, expected_embedding)
-    EmbeddingsGenerationStubs.discourse_service(described_class.name, text, expected_embedding)
+    EmbeddingsGenerationStubs.discourse_service(vector_rep.name, text, expected_embedding)
   end
 
   it_behaves_like "generates and store embedding using with vector representation"

spec/lib/modules/embeddings/vector_representations/multilingual_e5_large_spec.rb

@@ -11,7 +11,7 @@ RSpec.describe DiscourseAi::Embeddings::VectorRepresentations::MultilingualE5Lar
 
   def stub_vector_mapping(text, expected_embedding)
     EmbeddingsGenerationStubs.discourse_service(
-      described_class.name,
+      vector_rep.name,
       "query: #{text}",
       expected_embedding,
     )

spec/lib/modules/embeddings/vector_representations/text_embedding_ada_002_spec.rb

@@ -8,7 +8,7 @@ RSpec.describe DiscourseAi::Embeddings::VectorRepresentations::TextEmbeddingAda0
   let(:truncation) { DiscourseAi::Embeddings::Strategies::Truncation.new }
 
   def stub_vector_mapping(text, expected_embedding)
-    EmbeddingsGenerationStubs.openai_service(described_class.name, text, expected_embedding)
+    EmbeddingsGenerationStubs.openai_service(vector_rep.name, text, expected_embedding)
   end
 
   it_behaves_like "generates and store embedding using with vector representation"

spec/system/ai_helper/ai_composer_helper_spec.rb

@@ -327,10 +327,7 @@ RSpec.describe "AI Composer helper", type: :system, js: true do
   end
 
   context "when suggesting the category with AI category suggester" do
-    before do
+    before { SiteSetting.ai_embeddings_enabled = true }
-      SiteSetting.ai_embeddings_model = "bge-large-en"
-      SiteSetting.ai_embeddings_enabled = true
-    end
 
     it "updates the category with the suggested category" do
       response =
@@ -355,10 +352,7 @@ RSpec.describe "AI Composer helper", type: :system, js: true do
   end
 
   context "when suggesting the tags with AI tag suggester" do
-    before do
+    before { SiteSetting.ai_embeddings_enabled = true }
-      SiteSetting.ai_embeddings_model = "bge-large-en"
-      SiteSetting.ai_embeddings_enabled = true
-    end
 
     it "updates the tag with the suggested tag" do
       response =

spec/system/ai_helper/ai_split_topic_suggestion_spec.rb

@@ -80,10 +80,7 @@ RSpec.describe "AI Post helper", type: :system, js: true do
     end
 
     context "when suggesting categories with AI category suggester" do
-      before do
+      before { SiteSetting.ai_embeddings_enabled = true }
-        SiteSetting.ai_embeddings_model = "bge-large-en"
-        SiteSetting.ai_embeddings_enabled = true
-      end
 
       skip "TODO: Category suggester only loading one category in test" do
         it "updates the category with the suggested category" do
@@ -111,10 +108,7 @@ RSpec.describe "AI Post helper", type: :system, js: true do
     end
 
     context "when suggesting tags with AI tag suggester" do
-      before do
+      before { SiteSetting.ai_embeddings_enabled = true }
-        SiteSetting.ai_embeddings_model = "bge-large-en"
-        SiteSetting.ai_embeddings_enabled = true
-      end
 
       it "update the tag with the suggested tag" do
         response =

spec/system/embeddings/semantic_search_spec.rb

@@ -11,7 +11,6 @@ RSpec.describe "AI Composer helper", type: :system, js: true do
 
   before do
     SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
-    SiteSetting.ai_embeddings_model = "bge-large-en"
     prompt = DiscourseAi::Embeddings::HydeGenerators::OpenAi.new.prompt(query)
     OpenAiCompletionsInferenceStubs.stub_response(
       prompt,