# frozen_string_literal: true module DiscourseAi module Completions module Dialects class Gemini < Dialect class << self def can_translate?(model_provider) model_provider == "google" end end def native_tool_support? true end def translate # Gemini complains if we don't alternate model/user roles. noop_model_response = { role: "model", parts: { text: "Ok." } } messages = super interleving_messages = [] previous_message = nil system_instruction = nil messages.each do |message| if message[:role] == "system" system_instruction = message[:content] next end if previous_message if (previous_message[:role] == "user" || previous_message[:role] == "function") && message[:role] == "user" interleving_messages << noop_model_response.dup end end interleving_messages << message previous_message = message end { messages: interleving_messages, system_instruction: system_instruction } end def tools return if prompt.tools.blank? translated_tools = prompt.tools.map do |t| tool = t.slice(:name, :description) if t[:parameters] tool[:parameters] = t[:parameters].reduce( { type: "object", required: [], properties: {} }, ) do |memo, p| name = p[:name] memo[:required] << name if p[:required] memo[:properties][name] = p.except(:name, :required, :item_type) memo[:properties][name][:items] = { type: p[:item_type] } if p[:item_type] memo end end tool end [{ function_declarations: translated_tools }] end def max_prompt_tokens llm_model.max_prompt_tokens end protected def calculate_message_token(context) llm_model.tokenizer_class.size(context[:content].to_s + context[:name].to_s) end def beta_api? @beta_api ||= llm_model.name.start_with?("gemini-1.5") end def system_msg(msg) if beta_api? { role: "system", content: msg[:content] } else { role: "user", parts: { text: msg[:content] } } end end def model_msg(msg) if beta_api? { role: "model", parts: [{ text: msg[:content] }] } else { role: "model", parts: { text: msg[:content] } } end end def user_msg(msg) if beta_api? # support new format with multiple parts result = { role: "user", parts: [{ text: msg[:content] }] } return result unless vision_support? upload_parts = uploaded_parts(msg) result[:parts].concat(upload_parts) if upload_parts.present? result else { role: "user", parts: { text: msg[:content] } } end end def uploaded_parts(message) encoded_uploads = prompt.encoded_uploads(message) result = [] if encoded_uploads.present? encoded_uploads.each do |details| result << { inlineData: { mimeType: details[:mime_type], data: details[:base64] } } end end result end def tool_call_msg(msg) call_details = JSON.parse(msg[:content], symbolize_names: true) part = { functionCall: { name: msg[:name] || call_details[:name], args: call_details[:arguments], }, } if beta_api? { role: "model", parts: [part] } else { role: "model", parts: part } end end def tool_msg(msg) part = { functionResponse: { name: msg[:name] || msg[:id], response: { content: msg[:content], }, }, } if beta_api? { role: "function", parts: [part] } else { role: "function", parts: part } end end end end end end