discourse-ai/spec/jobs/scheduled/embeddings_backfill_spec.rb

56 lines
1.7 KiB
Ruby

# frozen_string_literal: true
RSpec.describe Jobs::EmbeddingsBackfill do
fab!(:second_topic) do
topic = Fabricate(:topic, created_at: 1.year.ago, bumped_at: 2.day.ago)
Fabricate(:post, topic: topic)
topic
end
fab!(:first_topic) do
topic = Fabricate(:topic, created_at: 1.year.ago, bumped_at: 1.day.ago)
Fabricate(:post, topic: topic)
topic
end
fab!(:third_topic) do
topic = Fabricate(:topic, created_at: 1.year.ago, bumped_at: 3.day.ago)
Fabricate(:post, topic: topic)
topic
end
let(:vector_rep) do
strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
end
it "backfills topics based on bumped_at date" do
SiteSetting.ai_embeddings_enabled = true
SiteSetting.ai_embeddings_discourse_service_api_endpoint = "http://test.com"
SiteSetting.ai_embeddings_backfill_batch_size = 1
Jobs.run_immediately!
embedding = Array.new(1024) { 1 }
WebMock.stub_request(
:post,
"#{SiteSetting.ai_embeddings_discourse_service_api_endpoint}/api/v1/classify",
).to_return(status: 200, body: JSON.dump(embedding))
Jobs::EmbeddingsBackfill.new.execute({})
topic_ids = DB.query_single("SELECT topic_id from #{vector_rep.topic_table_name}")
expect(topic_ids).to eq([first_topic.id])
# pulse again for the rest (and cover code)
SiteSetting.ai_embeddings_backfill_batch_size = 100
Jobs::EmbeddingsBackfill.new.execute({})
topic_ids = DB.query_single("SELECT topic_id from #{vector_rep.topic_table_name}")
expect(topic_ids).to contain_exactly(first_topic.id, second_topic.id, third_topic.id)
end
end