discourse-ai/spec/lib/modules/sentiment/entry_point_spec.rb

130 lines
4.1 KiB
Ruby

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