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4f1a3effe0
Both endpoints provide OpenAI-compatible servers. The only difference is that Vllm doesn't support passing tools as a separate parameter. Even if the tool param is supported, it ultimately relies on the model's ability to handle native functions, which is not the case with the models we have today. As a part of this change, we are dropping support for StableBeluga/Llama2 models. They don't have a chat_template, meaning the new API can translate them. These changes let us remove some of our existing dialects and are a first step in our plan to support any LLM by defining them as data-driven concepts. I rewrote the "translate" method to use a template method and extracted the tool support strategies into its classes to simplify the code. Finally, these changes bring support for Ollama when running in dev mode. It only works with Mistral for now, but it will change soon..
124 lines
3.8 KiB
Ruby
124 lines
3.8 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, model_name)
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endpoint_name == "anthropic" &&
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%w[claude-instant-1 claude-2 claude-3-haiku claude-3-opus claude-3-sonnet].include?(
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model_name,
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)
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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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options = { model: mapped_model, max_tokens: 3_000 }
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options[:stop_sequences] = ["</function_calls>"] if dialect.prompt.has_tools?
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options
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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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@uri ||= URI("https://api.anthropic.com/v1/messages")
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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
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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" => 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 final_log_update(log)
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log.request_tokens = @input_tokens if @input_tokens
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log.response_tokens = @output_tokens if @output_tokens
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end
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def extract_completion_from(response_raw)
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result = ""
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parsed = JSON.parse(response_raw, symbolize_names: true)
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if @streaming_mode
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if parsed[:type] == "content_block_start" || parsed[:type] == "content_block_delta"
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result = parsed.dig(:delta, :text).to_s
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elsif parsed[:type] == "message_start"
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@input_tokens = parsed.dig(:message, :usage, :input_tokens)
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elsif parsed[:type] == "message_delta"
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@output_tokens = parsed.dig(:delta, :usage, :output_tokens)
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end
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else
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result = parsed.dig(:content, 0, :text).to_s
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@input_tokens = parsed.dig(:usage, :input_tokens)
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@output_tokens = parsed.dig(:usage, :output_tokens)
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end
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result
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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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