mirror of
https://github.com/discourse/discourse-ai.git
synced 2025-02-12 22:44:45 +00:00
6ddc17fd61
Previous to this change we relied on explicit loading for a files in Discourse AI. This had a few downsides: - Busywork whenever you add a file (an extra require relative) - We were not keeping to conventions internally ... some places were OpenAI others are OpenAi - Autoloader did not work which lead to lots of full application broken reloads when developing. This moves all of DiscourseAI into a Zeitwerk compatible structure. It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there) To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
104 lines
3.2 KiB
Ruby
104 lines
3.2 KiB
Ruby
# frozen_string_literal: true
|
|
|
|
require "rails_helper"
|
|
require_relative "../../../support/nsfw_inference_stubs"
|
|
|
|
describe DiscourseAi::Nsfw::Classification do
|
|
before { SiteSetting.ai_nsfw_inference_service_api_endpoint = "http://test.com" }
|
|
|
|
let(:available_models) { SiteSetting.ai_nsfw_models.split("|") }
|
|
|
|
fab!(:upload_1) { Fabricate(:s3_image_upload) }
|
|
fab!(:post) { Fabricate(:post, uploads: [upload_1]) }
|
|
|
|
describe "#request" do
|
|
def assert_correctly_classified(results, expected)
|
|
available_models.each { |model| expect(results[model]).to eq(expected[model]) }
|
|
end
|
|
|
|
def build_expected_classification(target, positive: true)
|
|
available_models.reduce({}) do |memo, model|
|
|
model_expected =
|
|
if positive
|
|
NSFWInferenceStubs.positive_result(model)
|
|
else
|
|
NSFWInferenceStubs.negative_result(model)
|
|
end
|
|
|
|
memo[model] = {
|
|
target.id => model_expected.merge(target_classified_type: target.class.name),
|
|
}
|
|
memo
|
|
end
|
|
end
|
|
|
|
context "when the target has one upload" do
|
|
it "returns the classification and the model used for it" do
|
|
NSFWInferenceStubs.positive(upload_1)
|
|
expected = build_expected_classification(upload_1)
|
|
|
|
classification = subject.request(post)
|
|
|
|
assert_correctly_classified(classification, expected)
|
|
end
|
|
|
|
context "when the target has multiple uploads" do
|
|
fab!(:upload_2) { Fabricate(:upload) }
|
|
|
|
before { post.uploads << upload_2 }
|
|
|
|
it "returns a classification for each one" do
|
|
NSFWInferenceStubs.positive(upload_1)
|
|
NSFWInferenceStubs.negative(upload_2)
|
|
expected_classification = build_expected_classification(upload_1)
|
|
expected_classification.deep_merge!(
|
|
build_expected_classification(upload_2, positive: false),
|
|
)
|
|
|
|
classification = subject.request(post)
|
|
|
|
assert_correctly_classified(classification, expected_classification)
|
|
end
|
|
|
|
it "correctly skips unsupported uploads" do
|
|
NSFWInferenceStubs.positive(upload_1)
|
|
NSFWInferenceStubs.unsupported(upload_2)
|
|
expected_classification = build_expected_classification(upload_1)
|
|
|
|
classification = subject.request(post)
|
|
|
|
assert_correctly_classified(classification, expected_classification)
|
|
end
|
|
end
|
|
end
|
|
end
|
|
|
|
describe "#should_flag_based_on?" do
|
|
before { SiteSetting.ai_nsfw_flag_automatically = true }
|
|
|
|
let(:positive_verdict) { { "opennsfw2" => true, "nsfw_detector" => true } }
|
|
|
|
let(:negative_verdict) { { "opennsfw2" => false } }
|
|
|
|
it "returns false when NSFW flaggin is disabled" do
|
|
SiteSetting.ai_nsfw_flag_automatically = false
|
|
|
|
should_flag = subject.should_flag_based_on?(positive_verdict)
|
|
|
|
expect(should_flag).to eq(false)
|
|
end
|
|
|
|
it "returns true if the response is NSFW based on our thresholds" do
|
|
should_flag = subject.should_flag_based_on?(positive_verdict)
|
|
|
|
expect(should_flag).to eq(true)
|
|
end
|
|
|
|
it "returns false if the response is safe based on our thresholds" do
|
|
should_flag = subject.should_flag_based_on?(negative_verdict)
|
|
|
|
expect(should_flag).to eq(false)
|
|
end
|
|
end
|
|
end
|