# frozen_string_literal: true

RSpec.describe DiscourseAi::Summarization::FoldContent do
  subject(:summarizer) { DiscourseAi::Summarization.topic_summary(topic) }

  describe "#summarize" do
    let!(:llm_model) { assign_fake_provider_to(:ai_summarization_model) }

    fab!(:topic) { Fabricate(:topic, highest_post_number: 2) }
    fab!(:post_1) { Fabricate(:post, topic: topic, post_number: 1, raw: "This is a text") }

    before do
      SiteSetting.ai_summarization_enabled = true

      # Make sure each content fits in a single chunk.
      # 700 is the number of tokens reserved for the prompt.
      model_tokens =
        700 +
          DiscourseAi::Tokenizer::OpenAiTokenizer.size(
            "(1 #{post_1.user.username_lower} said: This is a text ",
          ) + 3

      llm_model.update!(max_prompt_tokens: model_tokens)
    end

    let(:single_summary) { "single" }
    let(:concatenated_summary) { "this is a concatenated summary" }

    fab!(:user)

    context "when the content to summarize fits in a single call" do
      it "does one call to summarize content" do
        result =
          DiscourseAi::Completions::Llm.with_prepared_responses([single_summary]) do |spy|
            summarizer.summarize(user).tap { expect(spy.completions).to eq(1) }
          end

        expect(result.summarized_text).to eq(single_summary)
      end
    end

    context "when the content to summarize doesn't fit in a single call" do
      fab!(:post_2) { Fabricate(:post, topic: topic, post_number: 2, raw: "This is a text") }

      it "keeps extending the summary until there is nothing else to process" do
        result =
          DiscourseAi::Completions::Llm.with_prepared_responses(
            [single_summary, concatenated_summary],
          ) { |spy| summarizer.summarize(user).tap { expect(spy.completions).to eq(2) } }

        expect(result.summarized_text).to eq(concatenated_summary)
      end
    end
  end
end