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

275 lines
8.3 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Endpoints
class Base
CompletionFailed = Class.new(StandardError)
TIMEOUT = 60
def self.endpoint_for(model_name)
# Order is important.
# Bedrock has priority over Anthropic if creadentials are present.
[
DiscourseAi::Completions::Endpoints::AwsBedrock,
DiscourseAi::Completions::Endpoints::Anthropic,
DiscourseAi::Completions::Endpoints::OpenAi,
DiscourseAi::Completions::Endpoints::HuggingFace,
DiscourseAi::Completions::Endpoints::Gemini,
DiscourseAi::Completions::Endpoints::Vllm,
].detect(-> { raise DiscourseAi::Completions::Llm::UNKNOWN_MODEL }) do |ek|
ek.can_contact?(model_name)
end
end
def self.can_contact?(_model_name)
raise NotImplementedError
end
def initialize(model_name, tokenizer)
@model = model_name
@tokenizer = tokenizer
end
def perform_completion!(dialect, user, model_params = {})
@streaming_mode = block_given?
prompt = dialect.translate
Net::HTTP.start(
model_uri.host,
model_uri.port,
use_ssl: true,
read_timeout: TIMEOUT,
open_timeout: TIMEOUT,
write_timeout: TIMEOUT,
) do |http|
response_data = +""
response_raw = +""
# Needed to response token calculations. Cannot rely on response_data due to function buffering.
partials_raw = +""
request_body = prepare_payload(prompt, model_params, dialect).to_json
request = prepare_request(request_body)
http.request(request) do |response|
if response.code.to_i != 200
Rails.logger.error(
"#{self.class.name}: status: #{response.code.to_i} - body: #{response.body}",
)
raise CompletionFailed
end
log =
AiApiAuditLog.new(
provider_id: provider_id,
user_id: user&.id,
raw_request_payload: request_body,
request_tokens: prompt_size(prompt),
)
if !@streaming_mode
response_raw = response.read_body
response_data = extract_completion_from(response_raw)
partials_raw = response_data.to_s
if has_tool?("", response_data)
function_buffer = build_buffer # Nokogiri document
function_buffer = add_to_buffer(function_buffer, "", response_data)
response_data = +function_buffer.at("function_calls").to_s
response_data << "\n"
end
return response_data
end
begin
cancelled = false
cancel = lambda { cancelled = true }
leftover = ""
function_buffer = build_buffer # Nokogiri document
prev_processed_partials = 0
response.read_body do |chunk|
if cancelled
http.finish
break
end
decoded_chunk = decode(chunk)
response_raw << decoded_chunk
redo_chunk = leftover + decoded_chunk
raw_partials = partials_from(redo_chunk)
raw_partials =
raw_partials[prev_processed_partials..-1] if prev_processed_partials > 0
if raw_partials.blank? || (raw_partials.size == 1 && raw_partials.first.blank?)
leftover = redo_chunk
next
end
json_error = false
raw_partials.each do |raw_partial|
json_error = false
prev_processed_partials += 1
next if cancelled
next if raw_partial.blank?
begin
partial = extract_completion_from(raw_partial)
next if partial.nil?
if has_tool?(response_data, partial)
function_buffer = add_to_buffer(function_buffer, response_data, partial)
if buffering_finished?(dialect.tools, function_buffer)
invocation = +function_buffer.at("function_calls").to_s
invocation << "\n"
partials_raw << partial.to_s
response_data << invocation
yield invocation, cancel
end
else
partials_raw << partial
response_data << partial
yield partial, cancel if partial
end
rescue JSON::ParserError
leftover = redo_chunk
json_error = true
end
end
if json_error
prev_processed_partials -= 1
else
leftover = ""
end
prev_processed_partials = 0 if leftover.blank?
end
rescue IOError, StandardError
raise if !cancelled
end
return response_data
ensure
if log
log.raw_response_payload = response_raw
log.response_tokens = tokenizer.size(partials_raw)
log.save!
if Rails.env.development?
puts "#{self.class.name}: request_tokens #{log.request_tokens} response_tokens #{log.response_tokens}"
end
end
end
end
end
def default_options
raise NotImplementedError
end
def provider_id
raise NotImplementedError
end
def prompt_size(prompt)
tokenizer.size(extract_prompt_for_tokenizer(prompt))
end
attr_reader :tokenizer
protected
attr_reader :model
def model_uri
raise NotImplementedError
end
def prepare_payload(_prompt, _model_params)
raise NotImplementedError
end
def prepare_request(_payload)
raise NotImplementedError
end
def extract_completion_from(_response_raw)
raise NotImplementedError
end
def decode(chunk)
chunk
end
def partials_from(_decoded_chunk)
raise NotImplementedError
end
def extract_prompt_for_tokenizer(prompt)
prompt
end
def build_buffer
Nokogiri::HTML5.fragment(<<~TEXT)
<function_calls>
<invoke>
<tool_name></tool_name>
<tool_id></tool_id>
<parameters>
</parameters>
</invoke>
</function_calls>
TEXT
end
def has_tool?(response, partial)
(response + partial).include?("<function_calls>")
end
def add_to_buffer(function_buffer, response_data, partial)
read_function = Nokogiri::HTML5.fragment(response_data + partial)
if tool_name = read_function.at("tool_name").text
function_buffer.at("tool_name").inner_html = tool_name
function_buffer.at("tool_id").inner_html = tool_name
end
read_parameters =
read_function
.at("parameters")
.elements
.each do |elem|
if paramenter = function_buffer.at(elem.name)&.text
function_buffer.at(elem.name).inner_html = paramenter
else
param_node = read_function.at(elem.name)
function_buffer.at("parameters").add_child(param_node)
function_buffer.at("parameters").add_child("\n")
end
end
function_buffer
end
def buffering_finished?(_available_functions, buffer)
buffer.to_s.include?("</function_calls>")
end
end
end
end
end