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