discourse-ai/lib/sentiment/sentiment_dashboard_report.rb

57 lines
1.9 KiB
Ruby

# 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
)
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")} AS sentiment_count
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)
ORDER BY 1 ASC
SQL
report_start: report.start_date,
report_end: report.end_date,
threshold: threshold,
)
return report if grouped_sentiments.empty?
report.data = {
req: "overall_sentiment",
color: report.colors[:lime],
label: I18n.t("discourse_ai.sentiment.reports.overall_sentiment"),
data:
grouped_sentiments.map do |gs|
{ x: gs.posted_at, y: gs.public_send("sentiment_count") }
end,
}
end
end
end
end
end