llm_feedback: Create an 'llm_feedback' object

In tidyprompt: Prompt Large Language Models and Enhance Their Functionality

Create an llm_feedback object

Description

This object is used to send feedback to a LLM when a LLM reply does not succesfully pass an extraction or validation function (as handled by send_prompt() and defined using prompt_wrap()). The feedback text is sent back to the LLM. The extraction or validation function should then return this object with the feedback text that should be sent to the LLM.

Usage

llm_feedback(text, tool_result = FALSE)

Arguments

text	A character string containing the feedback text. This will be sent back to the LLM after not passing an extractor or validator function
tool_result	A logical indicating whether the feedback is a tool result. If TRUE, send_prompt() will not remove it from the chat history when cleaning the context window during repeated interactions

Value

An object of class "llm_feedback" (or "llm_feedback_tool_result") containing the feedback text to send back to the LLM

See Also

llm_break()

Other prompt_wrap: llm_break(), prompt_wrap()

Other prompt_evaluation: llm_break(), send_prompt()

Examples

# Example usage within a validation function similar to the one in 'answer_as_integer()':
validation_fn <- function(x, min = 0, max = 100) {
  if (x != floor(x)) { # Not a whole number
    return(llm_feedback(
      "You must answer with only an integer (use no other characters)."
    ))
  }
  if (!is.null(min) && x < min) {
    return(llm_feedback(glue::glue(
      "The number should be greater than or equal to {min}."
    )))
  }
  if (!is.null(max) && x > max) {
    return(llm_feedback(glue::glue(
      "The number should be less than or equal to {max}."
    )))
  }
  return(TRUE)
}

# This validation_fn would be part of a prompt_wrap();
#   see the `answer_as_integer()` function for an example of how to use it

tidyprompt documentation built on April 4, 2025, 12:24 a.m.