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

68 lines
1.8 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Endpoints
class Vllm < Base
def self.can_contact?(model_name)
%w[mistralai/Mixtral-8x7B-Instruct-v0.1 mistralai/Mistral-7B-Instruct-v0.2].include?(
model_name,
)
end
def default_options
{ max_tokens_to_sample: 2000, model: model }
end
def provider_id
AiApiAuditLog::Provider::Vllm
end
private
def model_uri
service = DiscourseAi::Utils::DnsSrv.lookup(SiteSetting.ai_vllm_endpoint_srv)
if service.present?
api_endpoint = "https://#{service.target}:#{service.port}/v1/completions"
else
api_endpoint = "#{SiteSetting.ai_vllm_endpoint}/v1/completions"
end
@uri ||= URI(api_endpoint)
end
def prepare_payload(prompt, model_params, _dialect)
default_options
.merge(model_params)
.merge(prompt: prompt)
.tap { |payload| payload[:stream] = true if @streaming_mode }
end
def prepare_request(payload)
headers = { "Referer" => Discourse.base_url, "Content-Type" => "application/json" }
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
parsed.dig(:text)
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
end
end
end
end