89 lines
2.3 KiB
Ruby
89 lines
2.3 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Toxicity
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class ToxicityClassification
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CLASSIFICATION_LABELS = %i[
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toxicity
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severe_toxicity
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obscene
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identity_attack
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insult
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threat
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sexual_explicit
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]
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def type
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:toxicity
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end
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def can_classify?(target)
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content_of(target).present?
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end
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def get_verdicts(classification_data)
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# We only use one model for this classification.
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# Classification_data looks like { model_name => classification }
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_model_used, data = classification_data.to_a.first
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verdict =
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CLASSIFICATION_LABELS.any? do |label|
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data[label] >= SiteSetting.send("ai_toxicity_flag_threshold_#{label}")
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end
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{ available_model => verdict }
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end
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def should_flag_based_on?(verdicts)
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return false if !SiteSetting.ai_toxicity_flag_automatically
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verdicts.values.any?
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end
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def request(target_to_classify)
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data =
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::DiscourseAi::Inference::DiscourseClassifier.new(
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"#{endpoint}/api/v1/classify",
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SiteSetting.ai_toxicity_inference_service_api_key,
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SiteSetting.ai_toxicity_inference_service_api_model,
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).perform!(content_of(target_to_classify))
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{ available_model => data }
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end
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private
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def available_model
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SiteSetting.ai_toxicity_inference_service_api_model
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end
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def content_of(target_to_classify)
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content =
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if target_to_classify.is_a?(Chat::Message)
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target_to_classify.message
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else
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if target_to_classify.post_number == 1
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"#{target_to_classify.topic.title}\n#{target_to_classify.raw}"
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else
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target_to_classify.raw
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end
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end
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Tokenizer::BertTokenizer.truncate(content, 512)
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end
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def endpoint
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if SiteSetting.ai_toxicity_inference_service_api_endpoint_srv.present?
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service =
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DiscourseAi::Utils::DnsSrv.lookup(
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SiteSetting.ai_toxicity_inference_service_api_endpoint_srv,
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)
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"https://#{service.target}:#{service.port}"
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else
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SiteSetting.ai_toxicity_inference_service_api_endpoint
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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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