discourse-ai/lib/completions/endpoints/open_ai.rb

199 lines
5.8 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Endpoints
class OpenAi < Base
class << self
def can_contact?(endpoint_name, model_name)
return false unless endpoint_name == "open_ai"
%w[
gpt-3.5-turbo
gpt-4
gpt-3.5-turbo-16k
gpt-4-32k
gpt-4-0125-preview
gpt-4-turbo
].include?(model_name)
end
def dependant_setting_names
%w[
ai_openai_api_key
ai_openai_gpt4_32k_url
ai_openai_gpt4_turbo_url
ai_openai_gpt4_url
ai_openai_gpt4_url
ai_openai_gpt35_16k_url
ai_openai_gpt35_url
]
end
def correctly_configured?(model_name)
SiteSetting.ai_openai_api_key.present? && has_url?(model_name)
end
def has_url?(model)
url =
if model.include?("gpt-4")
if model.include?("32k")
SiteSetting.ai_openai_gpt4_32k_url
else
if model.include?("1106") || model.include?("turbo")
SiteSetting.ai_openai_gpt4_turbo_url
else
SiteSetting.ai_openai_gpt4_url
end
end
else
if model.include?("16k")
SiteSetting.ai_openai_gpt35_16k_url
else
SiteSetting.ai_openai_gpt35_url
end
end
url.present?
end
def endpoint_name(model_name)
"OpenAI - #{model_name}"
end
end
def normalize_model_params(model_params)
model_params = model_params.dup
# max_tokens, temperature are already supported
if model_params[:stop_sequences]
model_params[:stop] = model_params.delete(:stop_sequences)
end
model_params
end
def default_options
{ model: model == "gpt-4-turbo" ? "gpt-4-0125-preview" : model }
end
def provider_id
AiApiAuditLog::Provider::OpenAI
end
private
def model_uri
url =
if model.include?("gpt-4")
if model.include?("32k")
SiteSetting.ai_openai_gpt4_32k_url
else
if model.include?("1106") || model.include?("turbo")
SiteSetting.ai_openai_gpt4_turbo_url
else
SiteSetting.ai_openai_gpt4_url
end
end
else
if model.include?("16k")
SiteSetting.ai_openai_gpt35_16k_url
else
SiteSetting.ai_openai_gpt35_url
end
end
URI(url)
end
def prepare_payload(prompt, model_params, dialect)
default_options
.merge(model_params)
.merge(messages: prompt)
.tap do |payload|
payload[:stream] = true if @streaming_mode
payload[:tools] = dialect.tools if dialect.tools.present?
end
end
def prepare_request(payload)
headers =
{ "Content-Type" => "application/json" }.tap do |h|
if model_uri.host.include?("azure")
h["api-key"] = SiteSetting.ai_openai_api_key
else
h["Authorization"] = "Bearer #{SiteSetting.ai_openai_api_key}"
end
if SiteSetting.ai_openai_organization.present?
h["OpenAI-Organization"] = SiteSetting.ai_openai_organization
end
end
Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
end
def extract_completion_from(response_raw)
parsed = JSON.parse(response_raw, symbolize_names: true).dig(:choices, 0)
# half a line sent here
return if !parsed
response_h = @streaming_mode ? parsed.dig(:delta) : parsed.dig(:message)
@has_function_call ||= response_h.dig(:tool_calls).present?
@has_function_call ? response_h.dig(:tool_calls, 0) : response_h.dig(:content)
end
def partials_from(decoded_chunk)
decoded_chunk
.split("\n")
.map do |line|
data = line.split("data: ", 2)[1]
data == "[DONE]" ? nil : data
end
.compact
end
def extract_prompt_for_tokenizer(prompt)
prompt.map { |message| message[:content] || message["content"] || "" }.join("\n")
end
def has_tool?(_response_data)
@has_function_call
end
def add_to_buffer(function_buffer, _response_data, partial)
@args_buffer ||= +""
f_name = partial.dig(:function, :name)
function_buffer.at("tool_name").content = f_name if f_name
function_buffer.at("tool_id").content = partial[:id] if partial[:id]
if partial.dig(:function, :arguments).present?
@args_buffer << partial.dig(:function, :arguments)
begin
json_args = JSON.parse(@args_buffer, symbolize_names: true)
argument_fragments =
json_args.reduce(+"") do |memo, (arg_name, value)|
memo << "\n<#{arg_name}>#{value}</#{arg_name}>"
end
argument_fragments << "\n"
function_buffer.at("parameters").children =
Nokogiri::HTML5::DocumentFragment.parse(argument_fragments)
rescue JSON::ParserError
return function_buffer
end
end
function_buffer
end
end
end
end
end