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2be96e2098
Previously, sentiment and emotion classification only used configured classification model endpoints, which blocked sites that could not run those models. This change lets admins choose agent-backed LLM classifiers for sentiment and emotion while storing results under stable model keys so LLM changes do not force historic reclassification.
117 lines
3.7 KiB
Ruby
Vendored
117 lines
3.7 KiB
Ruby
Vendored
# frozen_string_literal: true
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module DiscourseAi
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module Agents
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class EmotionClassifier < Agent
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def self.default_enabled
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false
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end
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def system_prompt
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<<~PROMPT
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You classify Discourse forum posts by emotion.
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Return a probability score for every supported emotion label. Each score must be a float from 0 to 1. The scores must sum to 1.0. Higher scores mean the label is more applicable to the post.
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Classify the author's emotions, not quoted text or replies from other people. Ignore markup, links, signatures, logs, and code blocks unless they clearly express emotion. Interpret sarcasm and irony by their implied meaning.
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Multiple emotions can share probability mass, but the scores must still sum to 1.0. Use neutral as the highest score for factual announcements, questions, or technical debugging with little affect.
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Use the full post content provided by the user. Reply with valid JSON only. Do not include explanations, confidence fields, or any keys except the supported emotion labels.
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PROMPT
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end
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def response_format
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DiscourseAi::Sentiment::Emotions::LIST.map do |label|
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{ "key" => label, "type" => "number" }
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end
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end
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def examples
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[
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[
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"Thank you for the detailed walkthrough. This solved my issue and saved me a lot of time.",
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emotion_scores(
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gratitude: 0.72,
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admiration: 0.14,
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approval: 0.08,
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relief: 0.04,
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neutral: 0.02,
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),
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],
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[
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"This keeps failing after every deploy. I am frustrated that the same bug came back again.",
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emotion_scores(
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annoyance: 0.42,
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anger: 0.25,
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disappointment: 0.18,
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disapproval: 0.1,
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neutral: 0.05,
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),
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],
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[
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"Does anyone know why this setting disappeared after the migration?",
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emotion_scores(
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curiosity: 0.46,
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confusion: 0.32,
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surprise: 0.12,
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neutral: 0.08,
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realization: 0.02,
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),
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],
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[
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"I am sorry for deleting the topic by mistake. I should have checked before clicking.",
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emotion_scores(
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remorse: 0.68,
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embarrassment: 0.16,
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sadness: 0.08,
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disappointment: 0.05,
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neutral: 0.03,
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),
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],
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[
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"Great, now the backup is gone too. That is exactly what I needed today.",
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emotion_scores(
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annoyance: 0.35,
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anger: 0.22,
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disappointment: 0.2,
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disapproval: 0.12,
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sadness: 0.06,
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neutral: 0.05,
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),
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],
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[
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"I cannot believe how quickly this was fixed. The new workflow is a joy to use.",
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emotion_scores(
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joy: 0.42,
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admiration: 0.2,
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approval: 0.16,
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surprise: 0.12,
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excitement: 0.08,
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neutral: 0.02,
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),
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],
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[
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"I am worried the importer may lose attachments if we run it before the patch is ready.",
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emotion_scores(
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fear: 0.38,
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nervousness: 0.24,
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curiosity: 0.12,
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confusion: 0.1,
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neutral: 0.1,
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sadness: 0.06,
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),
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],
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]
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end
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private
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def emotion_scores(overrides)
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DiscourseAi::Sentiment::Emotions::LIST
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.index_with { |label| overrides[label.to_sym] || 0.0 }
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.to_json
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end
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end
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end
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end
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