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https://github.com/discourse/discourse-ai.git
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b2b01185f2
* FEATURE: add support for new OpenAI embedding models This adds support for just released text_embedding_3_small and large Note, we have not yet implemented truncation support which is a new API feature. (triggered using dimensions) * Tiny side fix, recalc bots when ai is enabled or disabled * FIX: downsample to 2000 items per vector which is a pgvector limitation
35 lines
1.0 KiB
Ruby
35 lines
1.0 KiB
Ruby
# frozen_string_literal: true
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module ::DiscourseAi
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module Inference
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class OpenAiEmbeddings
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def self.perform!(content, model:, dimensions: nil)
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headers = { "Content-Type" => "application/json" }
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if SiteSetting.ai_openai_embeddings_url.include?("azure")
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headers["api-key"] = SiteSetting.ai_openai_api_key
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else
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headers["Authorization"] = "Bearer #{SiteSetting.ai_openai_api_key}"
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end
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payload = { model: model, input: content }
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payload[:dimensions] = dimensions if dimensions.present?
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response = Faraday.post(SiteSetting.ai_openai_embeddings_url, payload.to_json, headers)
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case response.status
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when 200
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JSON.parse(response.body, symbolize_names: true)
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when 429
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# TODO add a AdminDashboard Problem?
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else
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Rails.logger.warn(
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"OpenAI Embeddings failed with status: #{response.status} body: #{response.body}",
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)
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raise Net::HTTPBadResponse
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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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