Detect Corpus Language With an LLM

Identifies the dominant language of a text sample by asking an LLM (OpenAI or Gemini) to pick one name from a candidate list. More accurate than detect_language() on short texts, mixed-language corpora, or languages with sparse snowball stopword coverage, at the cost of an API call.

Usage

detect_language_llm(
  texts,
  languages,
  provider = c("auto", "openai", "gemini"),
  model = NULL,
  api_key = NULL,
  sample_n = 200,
  seed = 123,
  verbose = TRUE
)

Arguments

texts

Character vector of documents.

languages

Named character vector of candidate languages (name = display name, value = language code), e.g. c(English = "en", French = "fr").

provider

One of "auto", "openai", "gemini". "auto" picks whichever of OPENAI_API_KEY / GEMINI_API_KEY is set, or the key implied by api_key's prefix.

model

Model name (default depends on provider).

api_key

API key; falls back to the provider's environment variable.

sample_n

Maximum documents to sample for the prompt (default 200).

seed

Seed for sampling.

verbose

Logical, print status messages (default TRUE).

Value

A one-row tibble with language (code) and provider, or NULL when no provider/key is available or the response doesn't match a candidate.

See also

detect_language() for the local, no-API alternative; call_llm_api() for the direct provider call.

Examples

if (interactive()) {
detect_language_llm(
  c("Bonjour, comment allez-vous?", "Je suis ravi de vous rencontrer."),
  languages = c(English = "en", French = "fr", Spanish = "es"),
  provider = "openai",
  api_key = Sys.getenv("OPENAI_API_KEY")
)
}