discourse-ai/lib/completions/dialects/chat_gpt.rb

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# frozen_string_literal: true
module DiscourseAi
module Completions
module Dialects
class ChatGpt < Dialect
class << self
def can_translate?(model_name)
%w[
gpt-3.5-turbo
gpt-4
gpt-3.5-turbo-16k
gpt-4-32k
gpt-4-1106-preview
gpt-4-turbo
].include?(model_name)
end
def tokenizer
DiscourseAi::Tokenizer::OpenAiTokenizer
end
end
def translate
messages = prompt.messages
# ChatGPT doesn't use an assistant msg to improve long-context responses.
messages.pop if messages.last[:type] == :model
trimmed_messages = trim_messages(messages)
trimmed_messages.map do |msg|
if msg[:type] == :system
{ role: "system", content: msg[:content] }
elsif msg[:type] == :model
{ role: "assistant", content: msg[:content] }
elsif msg[:type] == :tool_call
call_details = JSON.parse(msg[:content], symbolize_names: true)
call_details[:arguments] = call_details[:arguments].to_json
{
role: "assistant",
content: nil,
tool_calls: [{ type: "function", function: call_details, id: msg[:id] }],
}
elsif msg[:type] == :tool
{ role: "tool", tool_call_id: msg[:id], content: msg[:content] }
else
{ role: "user", content: msg[:content] }.tap do |user_msg|
user_msg[:name] = msg[:id] if msg[:id]
end
end
end
end
def tools
prompt.tools.map do |t|
tool = t.dup
tool[:parameters] = t[:parameters]
.to_a
.reduce({ type: "object", properties: {}, required: [] }) 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
{ type: "function", function: tool }
end
end
def max_prompt_tokens
# provide a buffer of 120 tokens - our function counting is not
# 100% accurate and getting numbers to align exactly is very hard
buffer = (opts[:max_tokens] || 2500) + 50
if tools.present?
# note this is about 100 tokens over, OpenAI have a more optimal representation
@function_size ||= self.class.tokenizer.size(tools.to_json.to_s)
buffer += @function_size
end
model_max_tokens - buffer
end
private
def per_message_overhead
# open ai defines about 4 tokens per message of overhead
4
end
def calculate_message_token(context)
self.class.tokenizer.size(context[:content].to_s + context[:name].to_s)
end
def model_max_tokens
case model_name
when "gpt-3.5-turbo-16k"
16_384
when "gpt-4"
8192
when "gpt-4-32k"
32_768
else
8192
end
end
end
end
end
end