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

121 lines
3.4 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Endpoints
class Anthropic < Base
class << self
def can_contact?(endpoint_name)
endpoint_name == "anthropic"
end
def dependant_setting_names
%w[ai_anthropic_api_key]
end
def correctly_configured?(_model_name)
SiteSetting.ai_anthropic_api_key.present?
end
def endpoint_name(model_name)
"Anthropic - #{model_name}"
end
end
def normalize_model_params(model_params)
# max_tokens, temperature, stop_sequences are already supported
model_params
end
def default_options(dialect)
# skipping 2.0 support for now, since other models are better
mapped_model =
case model
when "claude-2"
"claude-2.1"
when "claude-instant-1"
"claude-instant-1.2"
when "claude-3-haiku"
"claude-3-haiku-20240307"
when "claude-3-sonnet"
"claude-3-sonnet-20240229"
when "claude-3-opus"
"claude-3-opus-20240229"
else
raise "Unsupported model: #{model}"
end
{ model: mapped_model, max_tokens: 3_000 }
end
def provider_id
AiApiAuditLog::Provider::Anthropic
end
private
# this is an approximation, we will update it later if request goes through
def prompt_size(prompt)
tokenizer.size(prompt.system_prompt.to_s + " " + prompt.messages.to_s)
end
def model_uri
url = llm_model&.url || "https://api.anthropic.com/v1/messages"
URI(url)
end
def prepare_payload(prompt, model_params, dialect)
payload = default_options(dialect).merge(model_params).merge(messages: prompt.messages)
payload[:system] = prompt.system_prompt if prompt.system_prompt.present?
payload[:stream] = true if @streaming_mode
payload[:tools] = prompt.tools if prompt.tools.present?
payload
end
def prepare_request(payload)
headers = {
"anthropic-version" => "2023-06-01",
"x-api-key" => llm_model&.api_key || SiteSetting.ai_anthropic_api_key,
"content-type" => "application/json",
}
Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
end
def processor
@processor ||=
DiscourseAi::Completions::AnthropicMessageProcessor.new(streaming_mode: @streaming_mode)
end
def add_to_function_buffer(function_buffer, partial: nil, payload: nil)
processor.to_xml_tool_calls(function_buffer) if !partial
end
def extract_completion_from(response_raw)
processor.process_message(response_raw)
end
def has_tool?(_response_data)
processor.tool_calls.present?
end
def final_log_update(log)
log.request_tokens = processor.input_tokens if processor.input_tokens
log.response_tokens = processor.output_tokens if processor.output_tokens
end
def native_tool_support?
true
end
def partials_from(decoded_chunk)
decoded_chunk.split("\n").map { |line| line.split("data: ", 2)[1] }.compact
end
end
end
end
end