130 lines
4.1 KiB
Ruby
130 lines
4.1 KiB
Ruby
# frozen_string_literal: true
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require_relative "../../../support/sentiment_inference_stubs"
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RSpec.describe DiscourseAi::Sentiment::EntryPoint do
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fab!(:user) { Fabricate(:user, refresh_auto_groups: true) }
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describe "registering event callbacks" do
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context "when creating a post" do
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let(:creator) do
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PostCreator.new(
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user,
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raw: "this is the new content for my topic",
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title: "this is my new topic title",
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)
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end
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it "queues a job on create if sentiment analysis is enabled" do
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SiteSetting.ai_sentiment_enabled = true
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expect { creator.create }.to change(Jobs::PostSentimentAnalysis.jobs, :size).by(1)
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end
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it "does nothing if sentiment analysis is disabled" do
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SiteSetting.ai_sentiment_enabled = false
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expect { creator.create }.not_to change(Jobs::PostSentimentAnalysis.jobs, :size)
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end
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end
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context "when editing a post" do
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fab!(:post) { Fabricate(:post, user: user) }
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let(:revisor) { PostRevisor.new(post) }
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it "queues a job on update if sentiment analysis is enabled" do
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SiteSetting.ai_sentiment_enabled = true
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expect { revisor.revise!(user, raw: "This is my new test") }.to change(
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Jobs::PostSentimentAnalysis.jobs,
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:size,
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).by(1)
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end
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it "does nothing if sentiment analysis is disabled" do
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SiteSetting.ai_sentiment_enabled = false
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expect { revisor.revise!(user, raw: "This is my new test") }.not_to change(
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Jobs::PostSentimentAnalysis.jobs,
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:size,
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)
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end
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end
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end
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describe "custom reports" do
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before { SiteSetting.ai_sentiment_inference_service_api_endpoint = "http://test.com" }
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fab!(:pm) { Fabricate(:private_message_post) }
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fab!(:post_1) { Fabricate(:post) }
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fab!(:post_2) { Fabricate(:post) }
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describe "overall_sentiment report" do
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let(:positive_classification) { { negative: 2, neutral: 30, positive: 70 } }
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let(:negative_classification) { { negative: 65, neutral: 2, positive: 10 } }
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def sentiment_classification(post, classification)
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Fabricate(:sentiment_classification, target: post, classification: classification)
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end
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it "calculate averages using only public posts" do
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sentiment_classification(post_1, positive_classification)
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sentiment_classification(post_2, negative_classification)
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sentiment_classification(pm, positive_classification)
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report = Report.find("overall_sentiment")
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positive_data_point = report.data[0][:data].first[:y].to_i
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negative_data_point = report.data[1][:data].first[:y].to_i
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expect(positive_data_point).to eq(1)
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expect(negative_data_point).to eq(-1)
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end
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end
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describe "post_emotion report" do
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let(:emotion_1) do
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{ sadness: 49, surprise: 23, neutral: 6, fear: 34, anger: 87, joy: 22, disgust: 70 }
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end
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let(:emotion_2) do
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{ sadness: 19, surprise: 63, neutral: 45, fear: 44, anger: 27, joy: 62, disgust: 30 }
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end
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let(:model_used) { "emotion" }
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def emotion_classification(post, classification)
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Fabricate(
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:sentiment_classification,
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target: post,
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model_used: model_used,
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classification: classification,
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)
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end
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def strip_emoji_and_downcase(str)
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stripped_str = str.gsub(/[^\p{L}\p{N}]+/, "") # remove any non-alphanumeric characters
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stripped_str.downcase
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end
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it "calculate averages using only public posts" do
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threshold = 30
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emotion_classification(post_1, emotion_1)
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emotion_classification(post_2, emotion_2)
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emotion_classification(pm, emotion_2)
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report = Report.find("post_emotion")
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data_point = report.data
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data_point.each do |point|
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emotion = strip_emoji_and_downcase(point[:label])
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expected =
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(emotion_1[emotion.to_sym] > threshold ? 1 : 0) +
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(emotion_2[emotion.to_sym] > threshold ? 1 : 0)
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expect(point[:data][0][:y]).to eq(expected)
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end
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end
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end
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end
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end
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