discourse-ai/lib/embeddings/vector_representations/multilingual_e5_large.rb

58 lines
1.4 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Embeddings
module VectorRepresentations
class MultilingualE5Large < Base
def vector_from(text)
if DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured?
truncated_text = tokenizer.truncate(text, max_sequence_length - 2)
DiscourseAi::Inference::HuggingFaceTextEmbeddings.perform!(truncated_text).first
elsif SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
DiscourseAi::Inference::DiscourseClassifier.perform!(
"#{SiteSetting.ai_embeddings_discourse_service_api_endpoint}/api/v1/classify",
name,
"query: #{text}",
SiteSetting.ai_embeddings_discourse_service_api_key,
)
else
raise "No inference endpoint configured"
end
end
def id
3
end
def version
1
end
def name
"multilingual-e5-large"
end
def dimensions
1024
end
def max_sequence_length
512
end
def pg_function
"<=>"
end
def pg_index_type
"vector_cosine_ops"
end
def tokenizer
DiscourseAi::Tokenizer::MultilingualE5LargeTokenizer
end
end
end
end
end