# frozen_string_literal: true module DiscourseAi module Sentiment class SentimentDashboardReport def self.register!(plugin) plugin.add_report("overall_sentiment") do |report| report.modes = [:stacked_chart] threshold = 0.6 sentiment_count_sql = Proc.new { |sentiment| <<~SQL } COUNT( CASE WHEN (cr.classification::jsonb->'#{sentiment}')::float > :threshold THEN 1 ELSE NULL END ) AS #{sentiment}_count SQL grouped_sentiments = DB.query( <<~SQL, SELECT DATE_TRUNC('day', p.created_at)::DATE AS posted_at, #{sentiment_count_sql.call("positive")}, -#{sentiment_count_sql.call("negative")} FROM classification_results AS cr INNER JOIN posts p ON p.id = cr.target_id AND cr.target_type = 'Post' INNER JOIN topics t ON t.id = p.topic_id INNER JOIN categories c ON c.id = t.category_id WHERE t.archetype = 'regular' AND p.user_id > 0 AND cr.model_used = 'cardiffnlp/twitter-roberta-base-sentiment-latest' AND (p.created_at > :report_start AND p.created_at < :report_end) GROUP BY DATE_TRUNC('day', p.created_at) SQL report_start: report.start_date, report_end: report.end_date, threshold: threshold, ) data_points = %w[positive negative] return report if grouped_sentiments.empty? report.data = data_points.map do |point| { req: "sentiment_#{point}", color: point == "positive" ? report.colors[:lime] : report.colors[:purple], label: I18n.t("discourse_ai.sentiment.reports.overall_sentiment.#{point}"), data: grouped_sentiments.map do |gs| { x: gs.posted_at, y: gs.public_send("#{point}_count") } end, } end end end end end end