discourse-ai/lib/discourse_automation/llm_triage.rb

169 lines
5.3 KiB
Ruby

# frozen_string_literal: true
if defined?(DiscourseAutomation)
module DiscourseAutomation::LlmTriage
def self.handle(
post:,
model:,
search_for_text:,
system_prompt:,
category_id: nil,
tags: nil,
canned_reply: nil,
canned_reply_user: nil,
hide_topic: nil
)
if category_id.blank? && tags.blank? && canned_reply.blank? && hide_topic.blank?
raise ArgumentError, "llm_triage: no action specified!"
end
post_template = +""
post_template << "title: #{post.topic.title}\n"
post_template << "#{post.raw}"
filled_system_prompt = system_prompt.sub("%%POST%%", post_template)
if filled_system_prompt == system_prompt
raise ArgumentError, "llm_triage: system_prompt does not contain %%POST%% placeholder"
end
result = nil
if model == "claude-2"
# allowing double + 10 tokens
# technically maybe just token count is fine, but this will allow for more creative bad responses
result =
DiscourseAi::Inference::AnthropicCompletions.perform!(
filled_system_prompt,
model,
temperature: 0,
max_tokens:
DiscourseAi::Tokenizer::AnthropicTokenizer.tokenize(search_for_text).length * 2 + 10,
).dig(:completion)
else
result =
DiscourseAi::Inference::OpenAiCompletions.perform!(
[{ :role => "system", "content" => filled_system_prompt }],
model,
temperature: 0,
max_tokens:
DiscourseAi::Tokenizer::OpenAiTokenizer.tokenize(search_for_text).length * 2 + 10,
).dig(:choices, 0, :message, :content)
end
if result.strip == search_for_text.strip
user = User.find_by_username(canned_reply_user) if canned_reply_user.present?
user = user || Discourse.system_user
if canned_reply.present?
PostCreator.create!(
user,
topic_id: post.topic_id,
raw: canned_reply,
reply_to_post_number: post.post_number,
skip_validations: true,
)
end
changes = {}
changes[:category_id] = category_id if category_id.present?
changes[:tags] = tags if SiteSetting.tagging_enabled? && tags.present?
if changes.present?
first_post = post.topic.posts.where(post_number: 1).first
changes[:bypass_bump] = true
changes[:skip_validations] = true
first_post.revise(Discourse.system_user, changes)
end
post.topic.update!(visible: false) if hide_topic
end
end
end
DiscourseAutomation::Scriptable::LLM_TRIAGE = "llm_triage"
AVAILABLE_MODELS = [
{
id: "gpt-4",
name:
"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.gpt_4",
},
{
id: "gpt-3-5-turbo",
name:
"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.gpt_3_5_turbo",
},
{
id: "claude-2",
name:
"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.models.claude_2",
},
]
DiscourseAutomation::Scriptable.add(DiscourseAutomation::Scriptable::LLM_TRIAGE) do
version 1
run_in_background
placeholder :post
triggerables %i[post_created_edited]
field :system_prompt,
component: :message,
required: true,
validator: ->(input) do
if !input.include?("%%POST%%")
I18n.t(
"discourse_automation.scriptables.#{DiscourseAutomation::Scriptable::LLM_TRIAGE}.system_prompt_missing_post_placeholder",
)
end
end,
accepts_placeholders: true
field :search_for_text, component: :text, required: true
field :model, component: :choices, required: true, extra: { content: AVAILABLE_MODELS }
field :category, component: :category
field :tags, component: :tags
field :hide_topic, component: :boolean
field :canned_reply, component: :message
field :canned_reply_user, component: :user
script do |context, fields, automation|
post = context["post"]
system_prompt = fields["system_prompt"]["value"]
search_for_text = fields["search_for_text"]["value"]
model = fields["model"]["value"]
if !%w[gpt-4 gpt-3-5-turbo claude-2].include?(model)
Rails.logger.warn("llm_triage: model #{model} is not supported")
next
end
category_id = fields.dig("category", "value")
tags = fields.dig("tags", "value")
hide_topic = fields.dig("hide_topic", "value")
canned_reply = fields.dig("canned_reply", "value")
canned_reply_user = fields.dig("canned_reply_user", "value")
if post.raw.strip == canned_reply.to_s.strip
# nothing to do if we already replied
next
end
begin
DiscourseAutomation::LlmTriage.handle(
post: post,
model: model,
search_for_text: search_for_text,
system_prompt: system_prompt,
category_id: category_id,
tags: tags,
canned_reply: canned_reply,
canned_reply_user: canned_reply_user,
hide_topic: hide_topic,
)
rescue => e
Discourse.warn_exception(e, message: "llm_triage: failed to run inference")
end
end
end
end