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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..
171 lines
5.4 KiB
Ruby
171 lines
5.4 KiB
Ruby
# frozen_string_literal: true
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require "aws-sigv4"
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module DiscourseAi
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module Completions
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module Endpoints
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class AwsBedrock < Base
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class << self
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def can_contact?(endpoint_name, model_name)
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endpoint_name == "aws_bedrock" &&
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%w[claude-instant-1 claude-2 claude-3-haiku claude-3-sonnet claude-3-opus].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_bedrock_access_key_id ai_bedrock_secret_access_key ai_bedrock_region]
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end
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def correctly_configured?(model)
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SiteSetting.ai_bedrock_access_key_id.present? &&
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SiteSetting.ai_bedrock_secret_access_key.present? &&
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SiteSetting.ai_bedrock_region.present? && can_contact?("aws_bedrock", model)
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end
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def endpoint_name(model_name)
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"AWS Bedrock - #{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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model_params = model_params.dup
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# max_tokens, temperature, stop_sequences, top_p 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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options = { max_tokens: 3_000, anthropic_version: "bedrock-2023-05-31" }
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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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def prompt_size(prompt)
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# approximation
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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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# See: https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html
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#
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# FYI there is a 2.0 version of Claude, very little need to support it given
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# haiku/sonnet are better fits anyway, we map to claude-2.1
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bedrock_model_id =
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case model
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when "claude-2"
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"anthropic.claude-v2:1"
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when "claude-3-haiku"
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"anthropic.claude-3-haiku-20240307-v1:0"
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when "claude-3-sonnet"
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"anthropic.claude-3-sonnet-20240229-v1:0"
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when "claude-instant-1"
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"anthropic.claude-instant-v1"
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when "claude-3-opus"
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"anthropic.claude-3-opus-20240229-v1:0"
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end
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api_url =
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"https://bedrock-runtime.#{SiteSetting.ai_bedrock_region}.amazonaws.com/model/#{bedrock_model_id}/invoke"
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api_url = @streaming_mode ? (api_url + "-with-response-stream") : api_url
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URI(api_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
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end
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def prepare_request(payload)
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headers = { "content-type" => "application/json", "Accept" => "*/*" }
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signer =
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Aws::Sigv4::Signer.new(
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access_key_id: SiteSetting.ai_bedrock_access_key_id,
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region: SiteSetting.ai_bedrock_region,
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secret_access_key: SiteSetting.ai_bedrock_secret_access_key,
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service: "bedrock",
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)
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Net::HTTP::Post
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.new(model_uri)
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.tap do |r|
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r.body = payload
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signed_request =
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signer.sign_request(req: r, http_method: r.method, url: model_uri, body: r.body)
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r.initialize_http_header(headers.merge(signed_request.headers))
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end
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end
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def decode(chunk)
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parsed =
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Aws::EventStream::Decoder
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.new
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.decode_chunk(chunk)
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.first
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.payload
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.string
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.then { JSON.parse(_1) }
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bytes = parsed.dig("bytes")
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if !bytes
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Rails.logger.error("#{self.class.name}: #{parsed.to_s[0..500]}")
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nil
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else
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Base64.decode64(parsed.dig("bytes"))
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end
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rescue JSON::ParserError,
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Aws::EventStream::Errors::MessageChecksumError,
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Aws::EventStream::Errors::PreludeChecksumError => e
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Rails.logger.error("#{self.class.name}: #{e.message}")
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nil
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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]
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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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