Method to easily integrate to new LLM API's

Method to easily integrate to new LLM API's

Usage

ch_submit(
  defaults,
  prompt = NULL,
  stream = NULL,
  prompt_build = TRUE,
  preview = FALSE,
  ...
)

Arguments

defaults

Defaults object, generally puled from chattr_defaults()

prompt

The prompt to send to the LLM

stream

To output the response from the LLM as it happens, or wait until the response is complete. Defaults to TRUE.

prompt_build

Include the context and additional prompt as part of the request

preview

Primarily used for debugging. It indicates if it should send the prompt to the LLM (FALSE), or if it should print out the resulting prompt (TRUE)

...

Optional arguments; currently unused.

Value

The output from the model currently in use.

Details

Use this function to integrate your own LLM API. It has a few requirements to get it to work properly:

• The output of the function needs to be the parsed response from the LLM

• For those that support streaming, make sure to use the cat() function to output the response of the LLM API as it is happening.

• If preview is set to TRUE, do not send to the LLM API. Simply return the resulting prompt.

The defaults argument controls which method to use. You can use the chattr_defaults() function, and set the provider. The provider value is what creates the R class name. It will pre-pend cl_ to the class name. See the examples for more clarity.

Examples

if (FALSE) { # \dontrun{
library(chattr)
ch_submit.ch_my_llm <- function(defaults,
                                prompt = NULL,
                                stream = NULL,
                                prompt_build = TRUE,
                                preview = FALSE,
                                ...) {
  # Use `prompt_build` to append the prompts you with to append
  if (prompt_build) prompt <- paste0("Use the tidyverse\n", prompt)
  # If `preview` is true, return the resulting prompt back
  if (preview) {
    return(prompt)
  }
  llm_response <- paste0("You said this: \n", prompt)
  if (stream) {
    cat("streaming:\n")
    for (i in seq_len(nchar(llm_response))) {
      # If `stream` is true, make sure to `cat()` the current output
      cat(substr(llm_response, i, i))
      Sys.sleep(0.1)
    }
  }
  # Make sure to return the entire output from the LLM at the end
  llm_response
}

chattr_defaults("console", provider = "my llm")
chattr("hello")
chattr("hello", stream = FALSE)
chattr("hello", prompt_build = FALSE)
chattr("hello", preview = TRUE)
} # }