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https://github.com/discourse/discourse-ai.git
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6059b6e111
We enforced a hard limit of 700 tokens in this script, which is not enough when using thinking models, which can quickly use all of them. A temporary solution could be bumping the limit, but there is no guarantee we won't hit it again, and it's hard to find one value that fits all scenarios. Another alternative could be removing it and relying on the LLM config's `max_output_token`, but if you want different rules and want to assign different limits, you are forced to duplicate the config each time. Considering all this, we are adding a dedicated field for this in the triage script, giving you an easy way to tweak it to your needs. If empty, no limit is applied.
141 lines
4.4 KiB
Ruby
141 lines
4.4 KiB
Ruby
# frozen_string_literal: true
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if defined?(DiscourseAutomation)
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DiscourseAutomation::Scriptable.add("llm_triage") do
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version 1
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run_in_background
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placeholder :post
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triggerables %i[post_created_edited]
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# TODO move to triggerables
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field :include_personal_messages, component: :boolean
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# Inputs
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field :model,
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component: :choices,
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required: true,
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extra: {
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content: DiscourseAi::Automation.available_models,
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}
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field :system_prompt, component: :message, required: false
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field :search_for_text, component: :text, required: true
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field :max_post_tokens, component: :text
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field :stop_sequences, component: :text_list, required: false
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field :temperature, component: :text
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field :max_output_tokens, component: :text
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# Actions
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field :category, component: :category
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field :tags, component: :tags
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field :hide_topic, component: :boolean
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field :flag_post, component: :boolean
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field :flag_type,
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component: :choices,
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required: false,
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extra: {
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content: DiscourseAi::Automation.flag_types,
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},
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default: "review"
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field :canned_reply_user, component: :user
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field :canned_reply, component: :message
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field :reply_persona,
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component: :choices,
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extra: {
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content:
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DiscourseAi::Automation.available_persona_choices(
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require_user: false,
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require_default_llm: true,
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),
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}
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field :whisper, component: :boolean
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script do |context, fields|
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post = context["post"]
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next if post&.user&.bot?
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if post.topic.private_message?
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include_personal_messages = fields.dig("include_personal_messages", "value")
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next if !include_personal_messages
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end
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canned_reply = fields.dig("canned_reply", "value")
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canned_reply_user = fields.dig("canned_reply_user", "value")
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reply_persona_id = fields.dig("reply_persona", "value")
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whisper = fields.dig("whisper", "value")
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# nothing to do if we already replied
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next if post.user.username == canned_reply_user
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next if post.raw.strip == canned_reply.to_s.strip
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system_prompt = fields.dig("system_prompt", "value")
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search_for_text = fields.dig("search_for_text", "value")
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model = fields.dig("model", "value")
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category_id = fields.dig("category", "value")
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tags = fields.dig("tags", "value")
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hide_topic = fields.dig("hide_topic", "value")
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flag_post = fields.dig("flag_post", "value")
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flag_type = fields.dig("flag_type", "value")
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max_post_tokens = fields.dig("max_post_tokens", "value").to_i
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temperature = fields.dig("temperature", "value")
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if temperature == "" || temperature.nil?
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temperature = nil
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else
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temperature = temperature.to_f
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end
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max_output_tokens = fields.dig("max_output_tokens", "value").to_i
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max_output_tokens = nil if max_output_tokens <= 0
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max_post_tokens = nil if max_post_tokens <= 0
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stop_sequences = fields.dig("stop_sequences", "value")
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begin
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RateLimiter.new(
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Discourse.system_user,
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"llm_triage_#{post.id}",
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SiteSetting.ai_automation_max_triage_per_post_per_minute,
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1.minute,
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).performed!
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RateLimiter.new(
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Discourse.system_user,
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"llm_triage",
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SiteSetting.ai_automation_max_triage_per_minute,
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1.minute,
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).performed!
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DiscourseAi::Automation::LlmTriage.handle(
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post: post,
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model: model,
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search_for_text: search_for_text,
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system_prompt: system_prompt,
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category_id: category_id,
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tags: tags,
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canned_reply: canned_reply,
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canned_reply_user: canned_reply_user,
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reply_persona_id: reply_persona_id,
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whisper: whisper,
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hide_topic: hide_topic,
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flag_post: flag_post,
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flag_type: flag_type.to_s.to_sym,
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max_post_tokens: max_post_tokens,
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stop_sequences: stop_sequences,
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automation: self.automation,
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temperature: temperature,
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max_output_tokens: max_output_tokens,
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action: context["action"],
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)
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rescue => e
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Discourse.warn_exception(
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e,
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message: "llm_triage: skipped triage on post #{post.id} #{post.url}",
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)
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end
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end
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end
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end
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