Seed embedding definition from old settings

Author: romanrizzi

assets/javascripts/discourse/components/ai-embedding-editor.gjs

@@ -124,7 +124,7 @@ export default class AiEmbeddingEditor extends Component {
       await this.editingModel.save();
 
       if (isNew) {
-        this.args.embeddings.addObject(this.args.model);
+        this.args.embeddings.addObject(this.editingModel);
         this.router.transitionTo(
           "adminPlugins.show.discourse-ai-embeddings.index"
         );

db/migrate/20250110114305_embedding_config_data_migration.rb

@@ -0,0 +1,199 @@
+# frozen_string_literal: true
+
+class EmbeddingConfigDataMigration < ActiveRecord::Migration[7.0]
+  def up
+    current_model = fetch_setting("ai_embeddings_model") || "bge-large-en"
+    provider = provider_for(current_model)
+
+    if provider.present?
+      attrs = creds_for(provider)
+
+      if attrs.present?
+        attrs = attrs.merge(model_attrs(current_model))
+        attrs[:display_name] = current_model
+        attrs[:provider] = provider
+        persist_config(attrs)
+      end
+    end
+  end
+
+  def down
+  end
+
+  # Utils
+
+  def fetch_setting(name)
+    DB.query_single(
+      "SELECT value FROM site_settings WHERE name = :setting_name",
+      setting_name: name,
+    ).first || ENV["DISCOURSE_#{name&.upcase}"]
+  end
+
+  def provider_for(model)
+    cloudflare_api_token = fetch_setting("ai_cloudflare_workers_api_token")
+
+    return "cloudflare" if model == "bge-large-en" && cloudflare_api_token.present?
+
+    tei_models = %w[bge-large-en bge-m3 multilingual-e5-large]
+    return "hugging_face" if tei_models.include?(model)
+
+    return "google" if model == "gemini"
+
+    if %w[text-embedding-3-large text-embedding-3-small text-embedding-ada-002].include?(model)
+      return "open_ai"
+    end
+
+    nil
+  end
+
+  def creds_for(provider)
+    # CF
+    if provider == "cloudflare"
+      api_key = fetch_setting("ai_cloudflare_workers_api_token")
+      account_id = fetch_setting("ai_cloudflare_workers_account_id")
+
+      return if api_key.blank? || account_id.blank?
+
+      {
+        url:
+          "https://api.cloudflare.com/client/v4/accounts/#{account_id}/ai/run/@cf/baai/bge-large-en-v1.5",
+        api_key: api_key,
+      }
+      # TEI
+    elsif provider == "hugging_face"
+      endpoint = fetch_setting("ai_hugging_face_tei_endpoint")
+
+      if endpoint.blank?
+        endpoint = fetch_setting("ai_hugging_face_tei_endpoint_srv")
+        endpoint = "srv://#{endpoint}" if endpoint.present?
+      end
+
+      api_key = fetch_setting("ai_hugging_face_tei_api_key")
+
+      return if endpoint.blank? || api_key.blank?
+
+      { url: endpoint, api_key: api_key }
+      # Gemini
+    elsif provider == "google"
+      api_key = fetch_setting("ai_gemini_api_key")
+
+      return if api_key.blank?
+
+      {
+        url: "https://generativelanguage.googleapis.com/v1beta/models/embedding-001:embedContent",
+        api_key: api_key,
+      }
+
+      # Open AI
+    elsif provider == "open_ai"
+      endpoint = fetch_setting("ai_openai_embeddings_url")
+      api_key = fetch_setting("ai_openai_api_key")
+
+      return if endpoint.blank? || api_key.blank?
+
+      { url: endpoint, api_key: api_key }
+    else
+      nil
+    end
+  end
+
+  def model_attrs(model_name)
+    if model_name == "bge-large-en"
+      {
+        dimensions: 1024,
+        max_sequence_length: 512,
+        id: 4,
+        pg_function: "<#>",
+        tokenizer_class: "DiscourseAi::Tokenizer::BgeLargeEnTokenizer",
+      }
+    elsif model_name == "bge-m3"
+      {
+        dimensions: 1024,
+        max_sequence_length: 8192,
+        id: 8,
+        pg_function: "<#>",
+        tokenizer_class: "DiscourseAi::Tokenizer::BgeM3Tokenizer",
+      }
+    elsif model_name == "gemini"
+      {
+        dimensions: 768,
+        max_sequence_length: 1536,
+        id: 5,
+        pg_function: "<=>",
+        tokenizer_class: "DiscourseAi::Tokenizer::OpenAiTokenizer",
+      }
+    elsif model_name == "multilingual-e5-large"
+      {
+        dimensions: 1024,
+        max_sequence_length: 512,
+        id: 3,
+        pg_function: "<=>",
+        tokenizer_class: "DiscourseAi::Tokenizer::MultilingualE5LargeTokenizer",
+      }
+    elsif model_name == "text-embedding-3-large"
+      {
+        dimensions: 2000,
+        max_sequence_length: 8191,
+        id: 7,
+        pg_function: "<=>",
+        tokenizer_class: "DiscourseAi::Tokenizer::OpenAiTokenizer",
+        provider_params: {
+          model_name: "text-embedding-3-large",
+        },
+      }
+    elsif model_name == "text-embedding-3-small"
+      {
+        dimensions: 1536,
+        max_sequence_length: 8191,
+        id: 6,
+        pg_function: "<=>",
+        tokenizer_class: "DiscourseAi::Tokenizer::OpenAiTokenizer",
+        provider_params: {
+          model_name: "text-embedding-3-small",
+        },
+      }
+    else
+      {
+        dimensions: 1536,
+        max_sequence_length: 8191,
+        id: 2,
+        pg_function: "<=>",
+        tokenizer_class: "DiscourseAi::Tokenizer::OpenAiTokenizer",
+        provider_params: {
+          model_name: "text-embedding-ada-002",
+        },
+      }
+    end
+  end
+
+  def persist_config(attrs)
+    DB.exec(
+      <<~SQL,
+      INSERT INTO embedding_definitions (id, display_name, dimensions, max_sequence_length, version, pg_function, provider, tokenizer_class, url, api_key, provider_params, created_at, updated_at)
+      VALUES (:id, :display_name, :dimensions, :max_sequence_length, 1, :pg_function, :provider, :tokenizer_class, :url, :api_key, :provider_params, :now, :now)
+      SQL
+      id: attrs[:id],
+      display_name: attrs[:display_name],
+      dimensions: attrs[:dimensions],
+      max_sequence_length: attrs[:max_sequence_length],
+      pg_function: attrs[:pg_function],
+      provider: attrs[:provider],
+      tokenizer_class: attrs[:tokenizer_class],
+      url: attrs[:url],
+      api_key: attrs[:api_key],
+      provider_params: attrs[:provider_params],
+      now: Time.zone.now,
+    )
+
+    # We hardcoded the ID to match with already generated embeddings. Let's restart the seq to avoid conflicts.
+    DB.exec(
+      "ALTER SEQUENCE embedding_definitions_id_seq RESTART WITH :new_seq",
+      new_seq: attrs[:id].to_i + 1,
+    )
+
+    DB.exec(
+      "UPDATE site_settings SET value=:id WHERE name = 'ai_embeddings_selected_model'",
+      id: attrs[:id],
+    )
+  end
+end