57 lines
1.1 KiB
Ruby
57 lines
1.1 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 BgeM3 < Base
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class << self
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def name
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"bge-m3"
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end
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def correctly_configured?
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DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured?
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end
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def dependant_setting_names
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%w[ai_hugging_face_tei_endpoint_srv ai_hugging_face_tei_endpoint]
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end
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end
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def vector_from(text, asymetric: false)
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truncated_text = tokenizer.truncate(text, max_sequence_length - 2)
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DiscourseAi::Inference::HuggingFaceTextEmbeddings.perform!(truncated_text).first
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end
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def dimensions
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1024
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end
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def max_sequence_length
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8192
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end
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def id
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8
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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 pg_function
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"<#>"
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end
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def pg_index_type
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"vector_ip_ops"
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end
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def tokenizer
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DiscourseAi::Tokenizer::BgeM3Tokenizer
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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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