enterprise/app/models/response.rb
# == Schema Information
#
# Table name: responses
#
# id :bigint not null, primary key
# answer :text not null
# embedding :vector(1536)
# question :string not null
# status :integer default("pending")
# created_at :datetime not null
# updated_at :datetime not null
# account_id :bigint not null
# response_document_id :bigint
# response_source_id :bigint not null
#
# Indexes
#
# index_responses_on_embedding (embedding) USING ivfflat
# index_responses_on_response_document_id (response_document_id)
#
class Response < ApplicationRecord
belongs_to :response_document, optional: true
belongs_to :account
belongs_to :response_source
has_neighbors :embedding, normalize: true
before_save :update_response_embedding
before_validation :ensure_account
enum status: { pending: 0, active: 1 }
def self.search(query)
embedding = Openai::EmbeddingsService.new.get_embedding(query)
nearest_neighbors(:embedding, embedding, distance: 'cosine').first(5)
end
private
def ensure_account
self.account = response_source.account
end
def update_response_embedding
self.embedding = Openai::EmbeddingsService.new.get_embedding("#{question}: #{answer}")
end
end