discourse-ai/lib/completions/endpoints/open_ai.rb
Roman Rizzi 0634b85a81
UX: Validations to LLM-backed features (except AI Bot) (#436)
* UX: Validations to Llm-backed features (except AI Bot)

This change is part of an ongoing effort to prevent enabling a broken feature due to lack of configuration. We also want to explicit which provider we are going to use. For example, Claude models are available through AWS Bedrock and Anthropic, but the configuration differs.

Validations are:

* You must choose a model before enabling the feature.
* You must turn off the feature before setting the model to blank.
* You must configure each model settings before being able to select it.

* Add provider name to summarization options

* vLLM can technically support same models as HF

* Check we can talk to the selected model

* Check for Bedrock instead of anthropic as a site could have both creds setup
2024-01-29 16:04:25 -03:00

198 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