Language models as functions: the Claude API and ellmer — dragon_llm

Judges, teachers, and students in dragonfarm are plain functions from a character vector of prompts to a character vector of replies. These helpers build such functions.

Usage

dragon_llm_anthropic(
  model = "claude-opus-5",
  system = NULL,
  api_key = Sys.getenv("ANTHROPIC_API_KEY"),
  max_tokens = 1024,
  max_active = 4,
  temperature = NULL
)

dragon_judge_anthropic(
  model = "claude-opus-5",
  api_key = Sys.getenv("ANTHROPIC_API_KEY"),
  max_tokens = 1024,
  max_active = 4
)

dragon_llm_ellmer(chat, system = NULL)

dragon_judge_ellmer(chat)

Arguments

model: Claude model id. The default is the most capable general model; "claude-sonnet-5" or "claude-haiku-4-5" are cheaper choices for large prompt sets.
system: Optional system prompt.
api_key: Anthropic API key.
max_tokens: Reply length cap.
max_active: How many requests to run at once.
temperature: Sampling temperature, or NULL for the API default.
chat: An ellmer chat object, for example ellmer::chat_anthropic().

Value

A function suitable for the judge, teacher, or student arguments of dragon_judge(), dragon_synthesize(), and dragon_synthesize_pairs().

Details

dragon_llm_anthropic() calls the Claude API directly over HTTP with refusal fallbacks enabled, reading the key from ANTHROPIC_API_KEY. dragon_llm_ellmer() wraps any ellmer chat, so every provider ellmer supports works; each prompt gets a fresh copy of the chat so no history leaks between questions. The dragon_judge_*() variants are the same with a system prompt that asks for JSON-only answers, which dragon_judge() and dragon_synthesize_pairs() need.

Examples

if (interactive()) {
teacher <- dragon_llm_anthropic(system = "You are a concise support agent.")
teacher(c("My thermostat drops off Wi-Fi.", "Invoice total looks wrong."))
}