R/answer_by_chain_of_thought.R

In tidyprompt: Prompt Large Language Models and Enhance Their Functionality

#' @title Set chain of thought mode for a prompt
#'
#' @description This function enables chain of thought mode for evaluation of a prompt
#' or a [tidyprompt()]. In chain of thought mode, the large language model (LLM)
#' In chain of thought mode, the large language model (LLM) is asked to think
#' step by step to arrive at a final answer. It is hypothesized that this may
#' increase LLM performance at solving complex tasks. Chain of thought mode
#' is inspired by the method described in Wei et al. (2022).
#'
#' @param prompt A single string or a [tidyprompt()] object
#' @param extract_from_finish_brackets A logical indicating whether the final answer
#' should be extracted from the text inside the "FINISH[...]" brackets.
#' @param extraction_lenience A logical indcating whether the extraction function should be lenient.
#' If TRUE, the extraction function will attempt to extract the final answer
#' even if it cannot be extracted from within the brackets, by extracting
#' everything after the final occurence of 'FINISH' (if present). This may
#' be useful for smaller LLMs which may not follow the output format
#' as strictly
#'
#' @return A [tidyprompt()] with an added [prompt_wrap()] which will ensure
#' that the LLM follows the chain of thought mode in answering the prompt
#'
#' @export
#' @example inst/examples/answer_by_chain_of_thought.R
#'
#' @references
#' Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022).
#' Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.
#' <doi:10.48550/arXiv.2201.11903>
#'
#' @family pre_built_prompt_wraps
#' @family answer_by_prompt_wraps
answer_by_chain_of_thought <- function(
    prompt,
    extract_from_finish_brackets = TRUE,
    extraction_lenience = TRUE
) {

  # Define modification/extraction/validation functions:
  modify_fn <- function(original_prompt_text) {
    new_prompt <- glue::glue(
      "You are given a user's prompt.
      To answer the user's prompt, you need to think step by step to arrive at a final answer.

      ----- START OF USER'S PROMPT -----
      {original_prompt_text}
      ----- END OF USER'S PROMPT -----

      What are the steps you would take to answer the user's prompt?
      Describe your thought process in the following format:
        >> step 1: <step 1 description>
        >> step 2: <step 2 description>
        (etc.)"
    )

    if (extract_from_finish_brackets) {
      new_prompt <- glue::glue(
        "{new_prompt}

        When you are done, you must type:
          FINISH[<put here your final answer to the user's prompt>]

        Make sure your final answer follows the logical conclusion of your thought process."
      )
    }

    return(new_prompt)
  }

  extraction_fn <- function(llm_response) {
    if (!extract_from_finish_brackets)
      return(llm_response)
    extraction_fn_finish(llm_response, extraction_lenience)
  }

  prompt_wrap(
    prompt,
    modify_fn, extraction_fn,
    type = "mode", name = "answer_by_chain_of_thought"
  )
}