experiments.R
In LLMR: Interface for Large Language Model APIs in R

## -----------------------------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE, comment = "#>",
  eval = identical(tolower(Sys.getenv("LLMR_RUN_VIGNETTES", "false")), "true") )

## -----------------------------------------------------------------------------
library(LLMR)
library(dplyr)
cfg_openai <- llm_config("openai",   "gpt-5-nano")
cfg_cld    <- llm_config("anthropic","claude-sonnet-4-20250514", max_tokens = 512)
cfg_gem    <- llm_config("groq",     "openai/gpt-oss-20b")

## -----------------------------------------------------------------------------
experiments <- build_factorial_experiments(
  configs       = list(cfg_openai, cfg_cld, cfg_gem),
  user_prompts  = c("Summarize in one sentence: The Apollo program.",
                    "List two benefits of green tea."),
  system_prompts = c("Be concise.")
)
experiments

## -----------------------------------------------------------------------------
setup_llm_parallel(workers = 10)
res_unstructured <- call_llm_par(experiments, progress = TRUE)
reset_llm_parallel()
res_unstructured |>
  select(provider, model, user_prompt_label, response_text, finish_reason) |>
  head()

## -----------------------------------------------------------------------------
schema <- list(
  type = "object",
  properties = list(
    answer = list(type="string"),
    keywords = list(type="array", items = list(type="string"))
  ),
  required = list("answer","keywords"),
  additionalProperties = FALSE
)

experiments2 <- experiments
experiments2$config <- lapply(experiments2$config, enable_structured_output, schema = schema)

setup_llm_parallel(workers = 10)
res_structured <- call_llm_par_structured(experiments2 , .fields = c("answer","keywords") )
reset_llm_parallel()

res_structured |>
  select(provider, model, user_prompt_label, structured_ok, answer) |>
  head()