discourse-ai/lib/completions/dialects/nova.rb

178 lines
4.8 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Dialects
class Nova < Dialect
class << self
def can_translate?(llm_model)
llm_model.provider == "aws_bedrock" && llm_model.name.include?("amazon.nova")
end
end
class NovaPrompt
attr_reader :system, :messages, :inference_config, :tool_config
def initialize(system, messages, inference_config = nil, tool_config = nil)
@system = system
@messages = messages
@inference_config = inference_config
@tool_config = tool_config
end
def system_prompt
# small hack for size estimation
system.to_s
end
def has_tools?
tool_config.present?
end
def to_payload(options = nil)
stop_sequences = options[:stop_sequences]
max_tokens = options[:max_tokens]
inference_config = options&.slice(:temperature, :top_p, :top_k)
inference_config[:stopSequences] = stop_sequences if stop_sequences.present?
inference_config[:max_new_tokens] = max_tokens if max_tokens.present?
result = { system: system, messages: messages }
result[:inferenceConfig] = inference_config if inference_config.present?
result[:toolConfig] = tool_config if tool_config.present?
result
end
end
def translate
messages = super
system = messages.shift[:content] if messages.first&.dig(:role) == "system"
nova_messages = messages.map { |msg| { role: msg[:role], content: build_content(msg) } }
inference_config = build_inference_config
tool_config = tools_dialect.translated_tools if native_tool_support?
NovaPrompt.new(
system.presence && [{ text: system }],
nova_messages,
inference_config,
tool_config,
)
end
def max_prompt_tokens
llm_model.max_prompt_tokens
end
def native_tool_support?
!llm_model.lookup_custom_param("disable_native_tools")
end
def tools_dialect
if native_tool_support?
@tools_dialect ||= DiscourseAi::Completions::Dialects::NovaTools.new(prompt.tools)
else
super
end
end
private
def build_content(msg)
content = []
existing_content = msg[:content]
if existing_content.is_a?(Hash)
content << existing_content
elsif existing_content.is_a?(String)
content << { text: existing_content }
end
msg[:images]&.each { |image| content << image }
content
end
def build_inference_config
return unless opts[:inference_config]
config = {}
ic = opts[:inference_config]
config[:max_new_tokens] = ic[:max_new_tokens] if ic[:max_new_tokens]
config[:temperature] = ic[:temperature] if ic[:temperature]
config[:top_p] = ic[:top_p] if ic[:top_p]
config[:top_k] = ic[:top_k] if ic[:top_k]
config[:stopSequences] = ic[:stop_sequences] if ic[:stop_sequences]
config.present? ? config : nil
end
def detect_format(mime_type)
case mime_type
when "image/jpeg"
"jpeg"
when "image/png"
"png"
when "image/gif"
"gif"
when "image/webp"
"webp"
else
"jpeg" # default
end
end
def system_msg(msg)
msg = { role: "system", content: msg[:content] }
if tools_dialect.instructions.present?
msg[:content] = msg[:content].dup << "\n\n#{tools_dialect.instructions}"
end
msg
end
def user_msg(msg)
images = nil
if vision_support?
encoded_uploads = prompt.encoded_uploads(msg)
encoded_uploads&.each do |upload|
images ||= []
images << {
image: {
format: upload[:format] || detect_format(upload[:mime_type]),
source: {
bytes: upload[:base64],
},
},
}
end
end
{ role: "user", content: msg[:content], images: images }
end
def model_msg(msg)
{ role: "assistant", content: msg[:content] }
end
def tool_msg(msg)
translated = tools_dialect.from_raw_tool(msg)
{ role: "user", content: translated }
end
def tool_call_msg(msg)
translated = tools_dialect.from_raw_tool_call(msg)
{ role: "assistant", content: translated }
end
end
end
end
end