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2c0f535bab
* FEATURE: HyDE-powered semantic search. It relies on the new outlet added on discourse/discourse#23390 to display semantic search results in an unobtrusive way. We'll use a HyDE-backed approach for semantic search, which consists on generating an hypothetical document from a given keywords, which gets transformed into a vector and used in a asymmetric similarity topic search. This PR also reorganizes the internals to have less moving parts, maintaining one hierarchy of DAOish classes for vector-related operations like transformations and querying. Completions and vectors created by HyDE will remain cached on Redis for now, but we could later use Postgres instead. * Missing translation and rate limiting --------- Co-authored-by: Roman Rizzi <rizziromanalejandro@gmail.com>
41 lines
1.1 KiB
Ruby
41 lines
1.1 KiB
Ruby
# frozen_string_literal: true
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require "rails_helper"
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describe ::TopicsController do
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fab!(:topic) { Fabricate(:topic) }
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fab!(:topic1) { Fabricate(:topic) }
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fab!(:topic2) { Fabricate(:topic) }
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fab!(:topic3) { Fabricate(:topic) }
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fab!(:user) { Fabricate(:admin) }
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before do
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SiteSetting.ai_embeddings_semantic_related_topics_enabled = true
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SiteSetting.ai_embeddings_semantic_related_topics = 2
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end
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context "when a user is logged on" do
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it "includes related topics in payload when configured" do
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DiscourseAi::Embeddings::SemanticRelated
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.any_instance
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.stubs(:related_topic_ids_for)
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.returns([topic1.id, topic2.id, topic3.id])
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get("#{topic.relative_url}.json")
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expect(response.status).to eq(200)
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json = response.parsed_body
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expect(json["suggested_topics"].length).to eq(0)
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expect(json["related_topics"].length).to eq(2)
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sign_in(user)
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get("#{topic.relative_url}.json")
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json = response.parsed_body
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expect(json["suggested_topics"].length).to eq(0)
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expect(json["related_topics"].length).to eq(2)
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end
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end
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end
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