discourse-ai/lib/inference/amazon_bedrock_inference.rb

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# frozen_string_literal: true
require "base64"
require "json"
require "aws-eventstream"
require "aws-sigv4"
module ::DiscourseAi
module Inference
class AmazonBedrockInference
CompletionFailed = Class.new(StandardError)
TIMEOUT = 60
def self.perform!(
prompt,
model = "anthropic.claude-v2",
temperature: nil,
top_p: nil,
top_k: nil,
max_tokens: 20_000,
user_id: nil,
stop_sequences: nil,
tokenizer: Tokenizer::AnthropicTokenizer
)
raise CompletionFailed if model.blank?
raise CompletionFailed if !SiteSetting.ai_bedrock_access_key_id.present?
raise CompletionFailed if !SiteSetting.ai_bedrock_secret_access_key.present?
raise CompletionFailed if !SiteSetting.ai_bedrock_region.present?
signer =
Aws::Sigv4::Signer.new(
access_key_id: SiteSetting.ai_bedrock_access_key_id,
region: SiteSetting.ai_bedrock_region,
secret_access_key: SiteSetting.ai_bedrock_secret_access_key,
service: "bedrock",
)
log = nil
response_data = +""
response_raw = +""
url_api =
"https://bedrock-runtime.#{SiteSetting.ai_bedrock_region}.amazonaws.com/model/#{model}/"
if block_given?
url_api = url_api + "invoke-with-response-stream"
else
url_api = url_api + "invoke"
end
url = URI(url_api)
headers = { "content-type" => "application/json", "Accept" => "*/*" }
payload = { prompt: prompt }
payload[:top_p] = top_p if top_p
payload[:top_k] = top_k if top_k
payload[:max_tokens_to_sample] = max_tokens || 2000
payload[:temperature] = temperature if temperature
payload[:stop_sequences] = stop_sequences if stop_sequences
Net::HTTP.start(
url.host,
url.port,
use_ssl: true,
read_timeout: TIMEOUT,
open_timeout: TIMEOUT,
write_timeout: TIMEOUT,
) do |http|
request = Net::HTTP::Post.new(url)
request_body = payload.to_json
request.body = request_body
signed_request =
signer.sign_request(
req: request,
http_method: request.method,
url: url,
body: request.body,
)
request.initialize_http_header(headers.merge!(signed_request.headers))
http.request(request) do |response|
if response.code.to_i != 200
Rails.logger.error(
"BedRockInference: status: #{response.code.to_i} - body: #{response.body}",
)
raise CompletionFailed
end
log =
AiApiAuditLog.create!(
provider_id: AiApiAuditLog::Provider::Anthropic,
raw_request_payload: request_body,
user_id: user_id,
)
if !block_given?
response_body = response.read_body
parsed_response = JSON.parse(response_body, symbolize_names: true)
log.update!(
raw_response_payload: response_body,
request_tokens: tokenizer.size(prompt),
response_tokens: tokenizer.size(parsed_response[:completion]),
)
return parsed_response
end
begin
cancelled = false
cancel = lambda { cancelled = true }
decoder = Aws::EventStream::Decoder.new
response.read_body do |chunk|
if cancelled
http.finish
return
end
response_raw << chunk
begin
message = decoder.decode_chunk(chunk)
partial =
message
.first
.payload
.string
.then { JSON.parse(_1) }
.dig("bytes")
.then { Base64.decode64(_1) }
.then { JSON.parse(_1, symbolize_names: true) }
next if !partial
response_data << partial[:completion].to_s
yield partial, cancel if partial[:completion]
rescue JSON::ParserError,
Aws::EventStream::Errors::MessageChecksumError,
Aws::EventStream::Errors::PreludeChecksumError => e
Rails.logger.error("BedrockInference: #{e}")
end
rescue IOError
raise if !cancelled
end
end
return response_data
end
ensure
if block_given?
log.update!(
raw_response_payload: response_data,
request_tokens: tokenizer.size(prompt),
response_tokens: tokenizer.size(response_data),
)
end
if Rails.env.development? && log
puts "BedrockInference: request_tokens #{log.request_tokens} response_tokens #{log.response_tokens}"
end
end
end
end
end
end