fix(captain): require iterative vector scans

db/migrate/20260714230000_replace_captain_assistant_response_embedding_index_with_cosine.rb

@@ -0,0 +1,38 @@
+class ReplaceCaptainAssistantResponseEmbeddingIndexWithCosine < ActiveRecord::Migration[7.1]
+  disable_ddl_transaction!
+
+  OLD_INDEX_NAME = 'vector_idx_knowledge_entries_embedding'.freeze
+  NEW_INDEX_NAME = 'vector_idx_captain_assistant_responses_embedding_cosine'.freeze
+  MINIMUM_PGVECTOR_VERSION = Gem::Version.new('0.8.0')
+
+  def up
+    ensure_iterative_scans_supported!
+
+    add_index :captain_assistant_responses,
+              :embedding,
+              using: :ivfflat,
+              opclass: :vector_cosine_ops,
+              name: NEW_INDEX_NAME,
+              algorithm: :concurrently
+    remove_index :captain_assistant_responses, name: OLD_INDEX_NAME, algorithm: :concurrently
+  end
+
+  def down
+    add_index :captain_assistant_responses,
+              :embedding,
+              using: :ivfflat,
+              opclass: :vector_l2_ops,
+              name: OLD_INDEX_NAME,
+              algorithm: :concurrently
+    remove_index :captain_assistant_responses, name: NEW_INDEX_NAME, algorithm: :concurrently
+  end
+
+  private
+
+  def ensure_iterative_scans_supported!
+    installed_version = Gem::Version.new(select_value("SELECT extversion FROM pg_extension WHERE extname = 'vector'"))
+    return if installed_version >= MINIMUM_PGVECTOR_VERSION
+
+    raise StandardError, "pgvector #{MINIMUM_PGVECTOR_VERSION} or newer is required for filtered FAQ search"
+  end
+end

db/schema.rb

@@ -10,7 +10,7 @@
 #
 # It's strongly recommended that you check this file into your version control system.
 
-ActiveRecord::Schema[7.1].define(version: 2026_07_13_184351) do
+ActiveRecord::Schema[7.1].define(version: 2026_07_14_230000) do
   # These extensions should be enabled to support this database
   enable_extension "pg_stat_statements"
   enable_extension "pg_trgm"
@@ -361,7 +361,7 @@ ActiveRecord::Schema[7.1].define(version: 2026_07_13_184351) do
     t.index ["account_id"], name: "index_captain_assistant_responses_on_account_id"
     t.index ["assistant_id"], name: "index_captain_assistant_responses_on_assistant_id"
     t.index ["documentable_id", "documentable_type"], name: "idx_cap_asst_resp_on_documentable"
-    t.index ["embedding"], name: "vector_idx_knowledge_entries_embedding", using: :ivfflat
+    t.index ["embedding"], name: "vector_idx_captain_assistant_responses_embedding_cosine", opclass: :vector_cosine_ops, using: :ivfflat
     t.index ["status"], name: "index_captain_assistant_responses_on_status"
   end
 

enterprise/app/models/captain/assistant_response.rb

@@ -17,11 +17,11 @@
 #
 # Indexes
 #
-#  idx_cap_asst_resp_on_documentable                  (documentable_id,documentable_type)
+#  idx_cap_asst_resp_on_documentable                        (documentable_id,documentable_type)
-#  index_captain_assistant_responses_on_account_id    (account_id)
+#  index_captain_assistant_responses_on_account_id          (account_id)
-#  index_captain_assistant_responses_on_assistant_id  (assistant_id)
+#  index_captain_assistant_responses_on_assistant_id        (assistant_id)
-#  index_captain_assistant_responses_on_status        (status)
+#  index_captain_assistant_responses_on_status              (status)
-#  vector_idx_knowledge_entries_embedding             (embedding) USING ivfflat
+#  vector_idx_captain_assistant_responses_embedding_cosine  (embedding) USING ivfflat
 #
 class Captain::AssistantResponse < ApplicationRecord
   self.table_name = 'captain_assistant_responses'
@@ -48,7 +48,11 @@ class Captain::AssistantResponse < ApplicationRecord
 
   def self.search(query, account_id: nil)
     embedding = Captain::Llm::EmbeddingService.new(account_id: account_id).get_embedding(query)
-    nearest_neighbors(:embedding, embedding, distance: 'cosine').limit(5)
+
+    transaction do
+      connection.execute("SET LOCAL ivfflat.iterative_scan = 'relaxed_order'")
+      nearest_neighbors(:embedding, embedding, distance: 'cosine').limit(5).load
+    end
   end
 
   private