llm_fn: Apply an LLM prompt over vectors/data frames

In LLMR: Interface for Large Language Model APIs in R

Apply an LLM prompt over vectors/data frames

Description

Apply an LLM prompt over vectors/data frames

Usage

llm_fn(
  x,
  prompt,
  .config,
  .system_prompt = NULL,
  ...,
  .return = c("text", "columns", "object")
)

Arguments

x	A character vector or a data.frame/tibble.
prompt	A glue template string. With a data-frame you may reference columns ({col}); with a vector the placeholder is {x}.
.config	An llm_config object.
.system_prompt	Optional system message (character scalar).
...	Passed unchanged to call_llm_broadcast() (e.g. tries, progress, verbose).
.return	One of c("text","columns","object"). "columns" returns a tibble of diagnostic columns; "text" returns a character vector; "object" returns a list of llmr_response (or NA on failure).

Value

For generative mode:

• .return = "text": character vector

• .return = "columns": tibble with diagnostics

• .return = "object": list of llmr_response (or NA on failure) For embedding mode, always a numeric matrix.

See Also

llm_mutate(), llm_fn_structured(), setup_llm_parallel(), call_llm_broadcast(), get_batched_embeddings()

Examples

## Not run: 
words <- c("excellent", "awful")
cfg <- llm_config("openai", "gpt-4.1-nano", temperature = 0)
llm_fn(words, "Classify '{x}' as Positive/Negative.", cfg, .return = "text")

df <- tibble::tibble(text = words, source = c("review", "review"))
llm_fn(df, "Classify '{text}' from {source}.", cfg, .return = "columns")

## End(Not run)

LLMR documentation built on May 22, 2026, 1:07 a.m.