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

176 lines
4.7 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Dialects
class Dialect
class << self
def can_translate?(_model_name)
raise NotImplemented
end
def all_dialects
[
DiscourseAi::Completions::Dialects::ChatGpt,
DiscourseAi::Completions::Dialects::Gemini,
DiscourseAi::Completions::Dialects::Claude,
DiscourseAi::Completions::Dialects::Command,
DiscourseAi::Completions::Dialects::OpenAiCompatible,
]
end
def dialect_for(model_name)
dialects = []
if Rails.env.test? || Rails.env.development?
dialects = [DiscourseAi::Completions::Dialects::Fake]
end
dialects = dialects.concat(all_dialects)
dialect = dialects.find { |d| d.can_translate?(model_name) }
raise DiscourseAi::Completions::Llm::UNKNOWN_MODEL if !dialect
dialect
end
end
def initialize(generic_prompt, model_name, opts: {}, llm_model: nil)
@prompt = generic_prompt
@model_name = model_name
@opts = opts
@llm_model = llm_model
end
VALID_ID_REGEX = /\A[a-zA-Z0-9_]+\z/
def tokenizer
raise NotImplemented
end
def can_end_with_assistant_msg?
false
end
def native_tool_support?
false
end
def tools
@tools ||= tools_dialect.translated_tools
end
def translate
messages = prompt.messages
# Some models use an assistant msg to improve long-context responses.
if messages.last[:type] == :model && can_end_with_assistant_msg?
messages = messages.dup
messages.pop
end
trim_messages(messages).map { |msg| send("#{msg[:type]}_msg", msg) }.compact
end
def conversation_context
raise NotImplemented
end
def max_prompt_tokens
raise NotImplemented
end
attr_reader :prompt
private
attr_reader :model_name, :opts, :llm_model
def trim_messages(messages)
prompt_limit = max_prompt_tokens
current_token_count = 0
message_step_size = (max_prompt_tokens / 25).to_i * -1
trimmed_messages = []
range = (0..-1)
if messages.dig(0, :type) == :system
system_message = messages[0]
trimmed_messages << system_message
current_token_count += calculate_message_token(system_message)
range = (1..-1)
end
reversed_trimmed_msgs = []
messages[range].reverse.each do |msg|
break if current_token_count >= prompt_limit
message_tokens = calculate_message_token(msg)
dupped_msg = msg.dup
# Don't trim tool call metadata.
if msg[:type] == :tool_call
break if current_token_count + message_tokens + per_message_overhead > prompt_limit
current_token_count += message_tokens + per_message_overhead
reversed_trimmed_msgs << dupped_msg
next
end
# Trimming content to make sure we respect token limit.
while dupped_msg[:content].present? &&
message_tokens + current_token_count + per_message_overhead > prompt_limit
dupped_msg[:content] = dupped_msg[:content][0..message_step_size] || ""
message_tokens = calculate_message_token(dupped_msg)
end
next if dupped_msg[:content].blank?
current_token_count += message_tokens + per_message_overhead
reversed_trimmed_msgs << dupped_msg
end
reversed_trimmed_msgs.pop if reversed_trimmed_msgs.last&.dig(:type) == :tool
trimmed_messages.concat(reversed_trimmed_msgs.reverse)
end
def per_message_overhead
0
end
def calculate_message_token(msg)
self.tokenizer.size(msg[:content].to_s)
end
def tools_dialect
@tools_dialect ||= DiscourseAi::Completions::Dialects::XmlTools.new(prompt.tools)
end
def system_msg(msg)
raise NotImplemented
end
def assistant_msg(msg)
raise NotImplemented
end
def user_msg(msg)
raise NotImplemented
end
def tool_call_msg(msg)
{ role: "assistant", content: tools_dialect.from_raw_tool_call(msg) }
end
def tool_msg(msg)
{ role: "user", content: tools_dialect.from_raw_tool(msg) }
end
end
end
end
end