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

60 lines
1.3 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Embeddings
module VectorRepresentations
class Gemini < Base
class << self
def name
"gemini"
end
def correctly_configured?
SiteSetting.ai_gemini_api_key.present?
end
def dependant_setting_names
%w[ai_gemini_api_key]
end
end
def id
5
end
def version
1
end
def dimensions
768
end
def max_sequence_length
2048
end
def pg_function
"<=>"
end
def pg_index_type
"vector_cosine_ops"
end
def vector_from(text)
response = DiscourseAi::Inference::GeminiEmbeddings.perform!(text)
response[:embedding][:values]
end
# There is no public tokenizer for Gemini, and from the ones we already ship in the plugin
# OpenAI gets the closest results. Gemini Tokenizer results in ~10% less tokens, so it's safe
# to use OpenAI tokenizer since it will overestimate the number of tokens.
def tokenizer
DiscourseAi::Tokenizer::OpenAiTokenizer
end
end
end
end
end