98 lines
2.7 KiB
Ruby
98 lines
2.7 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 BgeLargeEn < Base
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class << self
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def name
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"bge-large-en"
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end
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def correctly_configured?
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SiteSetting.ai_cloudflare_workers_api_token.present? ||
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DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured? ||
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(
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SiteSetting.ai_embeddings_discourse_service_api_endpoint_srv.present? ||
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SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
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)
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end
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def dependant_setting_names
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%w[
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ai_cloudflare_workers_api_token
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ai_hugging_face_tei_endpoint_srv
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ai_hugging_face_tei_endpoint
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ai_embeddings_discourse_service_api_key
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ai_embeddings_discourse_service_api_endpoint_srv
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ai_embeddings_discourse_service_api_endpoint
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]
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end
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end
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def vector_from(text, asymetric: false)
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text = "#{asymmetric_query_prefix} #{text}" if asymetric
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client = inference_client
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needs_truncation = client.class.name.include?("HuggingFaceTextEmbeddings")
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text = tokenizer.truncate(text, max_sequence_length - 2) if needs_truncation
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inference_client.perform!(text)
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end
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def inference_model_name
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"baai/bge-large-en-v1.5"
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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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512
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end
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def id
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4
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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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"halfvec_ip_ops"
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end
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def tokenizer
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DiscourseAi::Tokenizer::BgeLargeEnTokenizer
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end
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def asymmetric_query_prefix
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"Represent this sentence for searching relevant passages:"
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end
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def inference_client
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if SiteSetting.ai_cloudflare_workers_api_token.present?
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DiscourseAi::Inference::CloudflareWorkersAi.instance(inference_model_name)
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elsif DiscourseAi::Inference::HuggingFaceTextEmbeddings.configured?
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DiscourseAi::Inference::HuggingFaceTextEmbeddings.instance
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elsif SiteSetting.ai_embeddings_discourse_service_api_endpoint_srv.present? ||
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SiteSetting.ai_embeddings_discourse_service_api_endpoint.present?
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DiscourseAi::Inference::DiscourseClassifier.instance(
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inference_model_name.split("/").last,
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)
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else
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raise "No inference endpoint configured"
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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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end
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