60 lines
1.4 KiB
Ruby
60 lines
1.4 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Embeddings
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module VectorRepresentations
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class Gemini < Base
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class << self
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def name
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"gemini"
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end
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def correctly_configured?
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SiteSetting.ai_gemini_api_key.present?
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end
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def dependant_setting_names
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%w[ai_gemini_api_key]
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end
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end
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def id
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5
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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 dimensions
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768
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end
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def max_sequence_length
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1536 # Gemini has a max sequence length of 2048, but the API has a limit of 10000 bytes, hence the lower value
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end
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def pg_function
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"<=>"
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end
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def pg_index_type
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"vector_cosine_ops"
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end
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def vector_from(text, asymetric: false)
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response = DiscourseAi::Inference::GeminiEmbeddings.perform!(text)
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response[:embedding][:values]
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end
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# There is no public tokenizer for Gemini, and from the ones we already ship in the plugin
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# OpenAI gets the closest results. Gemini Tokenizer results in ~10% less tokens, so it's safe
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# to use OpenAI tokenizer since it will overestimate the number of tokens.
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def tokenizer
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DiscourseAi::Tokenizer::OpenAiTokenizer
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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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