# frozen_string_literal: true require "aws-sigv4" module DiscourseAi module Completions module Endpoints class AwsBedrock < Base def self.can_contact?(model_provider) model_provider == "aws_bedrock" end def normalize_model_params(model_params) model_params = model_params.dup # max_tokens, temperature, stop_sequences, top_p are already supported model_params end def default_options(dialect) options = { max_tokens: 3_000, anthropic_version: "bedrock-2023-05-31" } options[:stop_sequences] = [""] if !dialect.native_tool_support? && dialect.prompt.has_tools? options end def provider_id AiApiAuditLog::Provider::Anthropic end def xml_tags_to_strip(dialect) if dialect.prompt.has_tools? %w[thinking search_quality_reflection search_quality_score] else [] end end private def prompt_size(prompt) # approximation tokenizer.size(prompt.system_prompt.to_s + " " + prompt.messages.to_s) end def model_uri region = llm_model.lookup_custom_param("region") bedrock_model_id = case llm_model.name when "claude-2" "anthropic.claude-v2:1" when "claude-3-haiku" "anthropic.claude-3-haiku-20240307-v1:0" when "claude-3-sonnet" "anthropic.claude-3-sonnet-20240229-v1:0" when "claude-instant-1" "anthropic.claude-instant-v1" when "claude-3-opus" "anthropic.claude-3-opus-20240229-v1:0" when "claude-3-5-sonnet" "anthropic.claude-3-5-sonnet-20240620-v1:0" else llm_model.name end if region.blank? || bedrock_model_id.blank? raise CompletionFailed.new(I18n.t("discourse_ai.llm_models.bedrock_invalid_url")) end api_url = "https://bedrock-runtime.#{region}.amazonaws.com/model/#{bedrock_model_id}/invoke" api_url = @streaming_mode ? (api_url + "-with-response-stream") : api_url URI(api_url) end def prepare_payload(prompt, model_params, dialect) @native_tool_support = dialect.native_tool_support? payload = default_options(dialect).merge(model_params).merge(messages: prompt.messages) payload[:system] = prompt.system_prompt if prompt.system_prompt.present? payload[:tools] = prompt.tools if prompt.has_tools? payload end def prepare_request(payload) headers = { "content-type" => "application/json", "Accept" => "*/*" } signer = Aws::Sigv4::Signer.new( access_key_id: llm_model.lookup_custom_param("access_key_id"), region: llm_model.lookup_custom_param("region"), secret_access_key: llm_model.api_key, service: "bedrock", ) Net::HTTP::Post .new(model_uri) .tap do |r| r.body = payload signed_request = signer.sign_request(req: r, http_method: r.method, url: model_uri, body: r.body) r.initialize_http_header(headers.merge(signed_request.headers)) end end def decode(chunk) @decoder ||= Aws::EventStream::Decoder.new decoded, _done = @decoder.decode_chunk(chunk) messages = [] return messages if !decoded i = 0 while decoded parsed = JSON.parse(decoded.payload.string) # perhaps some control message we can just ignore messages << Base64.decode64(parsed["bytes"]) if parsed && parsed["bytes"] decoded, _done = @decoder.decode_chunk i += 1 if i > 10_000 Rails.logger.error( "DiscourseAI: Stream decoder looped too many times, logic error needs fixing", ) break end end messages rescue JSON::ParserError, Aws::EventStream::Errors::MessageChecksumError, Aws::EventStream::Errors::PreludeChecksumError => e Rails.logger.error("#{self.class.name}: #{e.message}") nil 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 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 partials_from(decoded_chunks) decoded_chunks end def native_tool_support? @native_tool_support end def chunk_to_string(chunk) joined = +chunk.join("\n") joined << "\n" if joined.length > 0 joined end end end end end