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