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534b0df391
In a previous refactor, we moved the responsibility of querying and storing embeddings into the `Schema` class. Now, it's time for embedding generation. The motivation behind these changes is to isolate vector characteristics in simple objects to later replace them with a DB-backed version, similar to what we did with LLM configs.
90 lines
2.5 KiB
Ruby
90 lines
2.5 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Embeddings
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module Strategies
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class Truncation
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def id
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1
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end
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def version
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1
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end
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def prepare_target_text(target, vdef)
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max_length = vdef.max_sequence_length - 2
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case target
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when Topic
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topic_truncation(target, vdef.tokenizer, max_length)
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when Post
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post_truncation(target, vdef.tokenizer, max_length)
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when RagDocumentFragment
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vdef.tokenizer.truncate(target.fragment, max_length)
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else
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raise ArgumentError, "Invalid target type"
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end
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end
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def prepare_query_text(text, vdef, asymetric: false)
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qtext = asymetric ? "#{vdef.asymmetric_query_prefix} #{text}" : text
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max_length = vdef.max_sequence_length - 2
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vdef.tokenizer.truncate(text, max_length)
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end
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private
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def topic_information(topic)
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info = +""
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if topic&.title.present?
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info << topic.title
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info << "\n\n"
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end
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if topic&.category&.name.present?
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info << topic.category.name
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info << "\n\n"
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end
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if SiteSetting.tagging_enabled && topic&.tags.present?
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info << topic.tags.pluck(:name).join(", ")
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info << "\n\n"
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end
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info
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end
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def topic_truncation(topic, tokenizer, max_length)
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text = +topic_information(topic)
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if topic&.topic_embed&.embed_content_cache.present?
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text << Nokogiri::HTML5.fragment(topic.topic_embed.embed_content_cache).text
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text << "\n\n"
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end
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topic.posts.find_each do |post|
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text << Nokogiri::HTML5.fragment(post.cooked).text
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break if tokenizer.size(text) >= max_length #maybe keep a partial counter to speed this up?
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text << "\n\n"
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end
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tokenizer.truncate(text, max_length)
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end
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def post_truncation(post, tokenizer, max_length)
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text = +topic_information(post.topic)
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if post.is_first_post? && post.topic&.topic_embed&.embed_content_cache.present?
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text << Nokogiri::HTML5.fragment(post.topic.topic_embed.embed_content_cache).text
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else
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text << Nokogiri::HTML5.fragment(post.cooked).text
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end
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tokenizer.truncate(text, max_length)
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end
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end
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end
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end
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end
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