Sam 6ddc17fd61
DEV: port directory structure to Zeitwerk (#319)
Previous to this change we relied on explicit loading for a files in Discourse AI.

This had a few downsides:

- Busywork whenever you add a file (an extra require relative)
- We were not keeping to conventions internally ... some places were OpenAI others are OpenAi
- Autoloader did not work which lead to lots of full application broken reloads when developing.

This moves all of DiscourseAI into a Zeitwerk compatible structure.

It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there)

To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi

Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections

Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
2023-11-29 15:17:46 +11:00

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