discourse-ai/spec/lib/modules/embeddings/jobs/generate_embeddings_spec.rb

40 lines
1.2 KiB
Ruby

# frozen_string_literal: true
require_relative "../../../../support/embeddings_generation_stubs"
RSpec.describe Jobs::GenerateEmbeddings do
subject(:job) { described_class.new }
describe "#execute" do
before do
SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
SiteSetting.ai_embeddings_enabled = true
SiteSetting.ai_embeddings_model = "all-mpnet-base-v2"
end
fab!(:topic) { Fabricate(:topic) }
fab!(:post) { Fabricate(:post, post_number: 1, topic: topic) }
let(:truncation) { DiscourseAi::Embeddings::Strategies::Truncation.new }
let(:vector_rep) do
DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(truncation)
end
it "works" do
expected_embedding = [0.0038493] * vector_rep.dimensions
text =
truncation.prepare_text_from(
topic,
vector_rep.tokenizer,
vector_rep.max_sequence_length - 2,
)
EmbeddingsGenerationStubs.discourse_service(vector_rep.name, text, expected_embedding)
job.execute(topic_id: topic.id)
expect(vector_rep.topic_id_from_representation(expected_embedding)).to eq(topic.id)
end
end
end