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

63 lines
1.5 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Embeddings
module Strategies
class Truncation
def id
1
end
def version
1
end
def prepare_text_from(target, tokenizer, max_length)
case target
when Topic
topic_truncation(target, tokenizer, max_length)
when Post
post_truncation(target, tokenizer, max_length)
else
raise ArgumentError, "Invalid target type"
end
end
private
def topic_information(topic)
info = +""
info << topic.title
info << "\n\n"
info << topic.category.name if topic&.category&.name
if SiteSetting.tagging_enabled
info << "\n\n"
info << topic.tags.pluck(:name).join(", ")
end
info << "\n\n"
end
def topic_truncation(topic, tokenizer, max_length)
text = +topic_information(topic)
topic.posts.find_each do |post|
text << post.raw
break if tokenizer.size(text) >= max_length #maybe keep a partial counter to speed this up?
text << "\n\n"
end
tokenizer.truncate(text, max_length)
end
def post_truncation(topic, tokenizer, max_length)
text = +topic_information(post.topic)
text << post.raw
tokenizer.truncate(text, max_length)
end
end
end
end
end