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Previous to this change we relied on explicit loading for a files in Discourse AI. This had a few downsides: - Busywork whenever you add a file (an extra require relative) - We were not keeping to conventions internally ... some places were OpenAI others are OpenAi - Autoloader did not work which lead to lots of full application broken reloads when developing. This moves all of DiscourseAI into a Zeitwerk compatible structure. It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there) To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
149 lines
4.5 KiB
Ruby
149 lines
4.5 KiB
Ruby
# frozen_string_literal: true
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module ::DiscourseAi
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module Inference
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class HuggingFaceTextGeneration
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CompletionFailed = Class.new(StandardError)
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TIMEOUT = 120
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def self.perform!(
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prompt,
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model,
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temperature: 0.7,
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top_p: nil,
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top_k: nil,
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typical_p: nil,
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max_tokens: 2000,
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repetition_penalty: 1.1,
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user_id: nil,
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tokenizer: DiscourseAi::Tokenizer::Llama2Tokenizer,
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token_limit: nil
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)
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raise CompletionFailed if model.blank?
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url = URI(SiteSetting.ai_hugging_face_api_url)
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if block_given?
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url.path = "/generate_stream"
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else
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url.path = "/generate"
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end
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headers = { "Content-Type" => "application/json" }
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if SiteSetting.ai_hugging_face_api_key.present?
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headers["Authorization"] = "Bearer #{SiteSetting.ai_hugging_face_api_key}"
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end
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token_limit = token_limit || SiteSetting.ai_hugging_face_token_limit
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parameters = {}
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payload = { inputs: prompt, parameters: parameters }
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prompt_size = tokenizer.size(prompt)
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parameters[:top_p] = top_p if top_p
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parameters[:top_k] = top_k if top_k
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parameters[:typical_p] = typical_p if typical_p
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parameters[:max_new_tokens] = token_limit - prompt_size
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parameters[:temperature] = temperature if temperature
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parameters[:repetition_penalty] = repetition_penalty if repetition_penalty
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Net::HTTP.start(
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url.host,
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url.port,
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use_ssl: url.scheme == "https",
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read_timeout: TIMEOUT,
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open_timeout: TIMEOUT,
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write_timeout: TIMEOUT,
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) do |http|
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request = Net::HTTP::Post.new(url, headers)
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request_body = payload.to_json
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request.body = request_body
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http.request(request) do |response|
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if response.code.to_i != 200
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Rails.logger.error(
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"HuggingFaceTextGeneration: status: #{response.code.to_i} - body: #{response.body}",
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)
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raise CompletionFailed
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end
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log =
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AiApiAuditLog.create!(
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provider_id: AiApiAuditLog::Provider::HuggingFaceTextGeneration,
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raw_request_payload: request_body,
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user_id: user_id,
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)
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if !block_given?
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response_body = response.read_body
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parsed_response = JSON.parse(response_body, symbolize_names: true)
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log.update!(
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raw_response_payload: response_body,
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request_tokens: tokenizer.size(prompt),
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response_tokens: tokenizer.size(parsed_response[:generated_text]),
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)
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return parsed_response
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end
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response_data = +""
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begin
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cancelled = false
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cancel = lambda { cancelled = true }
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response_raw = +""
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response.read_body do |chunk|
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if cancelled
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http.finish
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return
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end
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response_raw << chunk
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chunk
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.split("\n")
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.each do |line|
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data = line.split("data:", 2)[1]
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next if !data || data.squish == "[DONE]"
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if !cancelled
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begin
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# partial contains the entire payload till now
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partial = JSON.parse(data, symbolize_names: true)
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# this is the last chunk and contains the full response
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next if partial[:token][:special] == true
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response_data << partial[:token][:text].to_s
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yield partial, cancel
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rescue JSON::ParserError
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nil
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end
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end
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end
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rescue IOError
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raise if !cancelled
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ensure
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log.update!(
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raw_response_payload: response_raw,
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request_tokens: tokenizer.size(prompt),
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response_tokens: tokenizer.size(response_data),
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)
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end
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end
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return response_data
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end
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end
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def self.try_parse(data)
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JSON.parse(data, symbolize_names: true)
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rescue JSON::ParserError
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nil
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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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