2023-12-15 12:32:01 -05:00
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# frozen_string_literal: true
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module DiscourseAi
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module Completions
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module Endpoints
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class Gemini < Base
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class << self
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def can_contact?(endpoint_name)
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endpoint_name == "google"
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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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def correctly_configured?(_model_name)
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SiteSetting.ai_gemini_api_key.present?
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end
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def endpoint_name(model_name)
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"Google - #{model_name}"
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end
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end
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def default_options
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{ generationConfig: {} }
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end
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def normalize_model_params(model_params)
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model_params = model_params.dup
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if model_params[:stop_sequences]
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model_params[:stopSequences] = model_params.delete(:stop_sequences)
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end
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if model_params[:max_tokens]
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model_params[:maxOutputTokens] = model_params.delete(:max_tokens)
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end
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model_params[:topP] = model_params.delete(:top_p) if model_params[:top_p]
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# temperature already supported
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model_params
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end
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def provider_id
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AiApiAuditLog::Provider::Gemini
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end
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private
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def model_uri
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if llm_model
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url = llm_model.url
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else
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mapped_model = model
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if model == "gemini-1.5-pro"
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mapped_model = "gemini-1.5-pro-latest"
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elsif model == "gemini-1.5-flash"
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mapped_model = "gemini-1.5-flash-latest"
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elsif model == "gemini-1.0-pro"
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mapped_model = "gemini-pro-latest"
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end
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url = "https://generativelanguage.googleapis.com/v1beta/models/#{mapped_model}"
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end
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key = llm_model&.api_key || SiteSetting.ai_gemini_api_key
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if @streaming_mode
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url = "#{url}:streamGenerateContent?key=#{key}&alt=sse"
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else
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url = "#{url}:generateContent?key=#{key}"
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end
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URI(url)
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end
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def prepare_payload(prompt, model_params, dialect)
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tools = dialect.tools
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payload = default_options.merge(contents: prompt[:messages])
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payload[:systemInstruction] = {
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role: "system",
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parts: [{ text: prompt[:system_instruction].to_s }],
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} if prompt[:system_instruction].present?
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payload[:tools] = tools if tools.present?
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payload[:generationConfig].merge!(model_params) if model_params.present?
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payload
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end
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def prepare_request(payload)
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headers = { "Content-Type" => "application/json" }
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Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
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end
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def extract_completion_from(response_raw)
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parsed =
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if @streaming_mode
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response_raw
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else
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JSON.parse(response_raw, symbolize_names: true)
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end
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response_h = parsed.dig(:candidates, 0, :content, :parts, 0)
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@has_function_call ||= response_h.dig(:functionCall).present?
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@has_function_call ? response_h[:functionCall] : response_h.dig(:text)
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end
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def partials_from(decoded_chunk)
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decoded_chunk
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end
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def chunk_to_string(chunk)
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chunk.to_s
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end
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class Decoder
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def initialize
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@buffer = +""
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end
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def decode(str)
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@buffer << str
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lines = @buffer.split(/\r?\n\r?\n/)
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keep_last = false
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decoded =
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lines
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.map do |line|
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if line.start_with?("data: {")
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begin
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JSON.parse(line[6..-1], symbolize_names: true)
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rescue JSON::ParserError
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keep_last = line
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nil
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end
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else
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keep_last = line
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nil
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end
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end
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.compact
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if keep_last
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@buffer = +(keep_last)
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else
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@buffer = +""
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end
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decoded
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end
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end
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def decode(chunk)
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@decoder ||= Decoder.new
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@decoder.decode(chunk)
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end
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def extract_prompt_for_tokenizer(prompt)
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prompt.to_s
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end
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2024-01-02 09:21:13 -05:00
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def has_tool?(_response_data)
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@has_function_call
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end
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def native_tool_support?
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true
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end
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def add_to_function_buffer(function_buffer, payload: nil, partial: nil)
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if @streaming_mode
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return function_buffer if !partial
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else
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partial = payload
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end
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function_buffer.at("tool_name").content = partial[:name] if partial[:name].present?
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if partial[:args]
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argument_fragments =
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partial[:args].reduce(+"") do |memo, (arg_name, value)|
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memo << "\n<#{arg_name}>#{value}</#{arg_name}>"
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end
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argument_fragments << "\n"
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function_buffer.at("parameters").children =
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Nokogiri::HTML5::DocumentFragment.parse(argument_fragments)
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end
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function_buffer
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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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