44 lines
1.3 KiB
Ruby
44 lines
1.3 KiB
Ruby
# frozen_string_literal: true
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RSpec.describe Jobs::GenerateEmbeddings do
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subject(:job) { described_class.new }
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fab!(:vector_def) { Fabricate(:embedding_definition) }
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describe "#execute" do
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before do
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SiteSetting.ai_embeddings_selected_model = vector_def.id
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SiteSetting.ai_embeddings_enabled = true
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end
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fab!(:topic)
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fab!(:post) { Fabricate(:post, post_number: 1, topic: topic) }
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let(:topics_schema) { DiscourseAi::Embeddings::Schema.for(Topic) }
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let(:posts_schema) { DiscourseAi::Embeddings::Schema.for(Post) }
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it "works for topics" do
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expected_embedding = [0.0038493] * vector_def.dimensions
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text = vector_def.prepare_target_text(topic)
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EmbeddingsGenerationStubs.hugging_face_service(text, expected_embedding)
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job.execute(target_id: topic.id, target_type: "Topic")
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expect(topics_schema.find_by_embedding(expected_embedding).topic_id).to eq(topic.id)
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end
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it "works for posts" do
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expected_embedding = [0.0038493] * vector_def.dimensions
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text = vector_def.prepare_target_text(post)
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EmbeddingsGenerationStubs.hugging_face_service(text, expected_embedding)
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job.execute(target_id: post.id, target_type: "Post")
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expect(posts_schema.find_by_embedding(expected_embedding).post_id).to eq(post.id)
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end
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end
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end
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