Module: RCrewAI::Similarity

Defined in:
lib/rcrewai/similarity.rb

Overview

Similarity measures shared across Knowledge and Memory. cosine compares embedding vectors; lexical is the word-overlap fallback used when no embedder is available.

Constant Summary collapse

STOPWORDS = 
%w[the a an and or but in on at to for of with by is are was were be].freeze

Class Method Summary collapse

Class Method Details

.cosine(vec_a, vec_b) ⇒ Object 



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# File 'lib/rcrewai/similarity.rb', line 12

def cosine(vec_a, vec_b)
  dot = 0.0
  norm_a = 0.0
  norm_b = 0.0
  length = [vec_a.length, vec_b.length].max
  length.times do |i|
    ai = (vec_a[i] || 0).to_f
    bi = (vec_b[i] || 0).to_f
    dot += ai * bi
    norm_a += ai * ai
    norm_b += bi * bi
  end
  return 0.0 if norm_a.zero? || norm_b.zero?

  dot / (Math.sqrt(norm_a) * Math.sqrt(norm_b))
end

.keywords(text) ⇒ Object 



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# File 'lib/rcrewai/similarity.rb', line 39

def keywords(text)
  text.to_s.downcase.split(/\W+/).reject { |w| w.length < 3 || STOPWORDS.include?(w) }
end

.lexical(text_a, text_b) ⇒ Object

Jaccard-style overlap of content words. Cheap, no embeddings.



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# File 'lib/rcrewai/similarity.rb', line 30

def lexical(text_a, text_b)
  words_a = keywords(text_a)
  words_b = keywords(text_b)
  union = (words_a | words_b).length
  return 0.0 if union.zero?

  (words_a & words_b).length.to_f / union
end