inst/doc/chat-basics.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)

cfg_openai <- llm_config(
  provider = "openai",
  model    = "gpt-5-nano",
  
)

chat_oai <- chat_session(cfg_openai, system = "Be concise.")
chat_oai$send("Say a warm hello in one short sentence.")
chat_oai$send("Now say it in Esperanto.")

## -----------------------------------------------------------------------------
cfg_anthropic <- llm_config(
  provider = "anthropic",
  model    = "claude-sonnet-4-20250514",
  max_tokens = 512   # avoid warnings; Anthropic requires max_tokens
)

chat_claude <- chat_session(cfg_anthropic, system = "Be concise.")
chat_claude$send("Name one interesting fact about honey bees.")

## -----------------------------------------------------------------------------
cfg_gemini <- llm_config(
  provider = "gemini",
  model    = "gemini-2.5-flash",
  
)

chat_gem <- chat_session(cfg_gemini, system = "Be concise.")
chat_gem$send("Give me a single-sentence fun fact about volcanoes.")

## -----------------------------------------------------------------------------
cfg_groq <- llm_config(
  provider = "groq",
  model    = "openai/gpt-oss-20b",
  
)

chat_groq <- chat_session(cfg_groq, system = "Be concise.")
chat_groq$send("Share a short fun fact about octopuses.")

## -----------------------------------------------------------------------------
schema <- list(
  type = "object",
  properties = list(
    answer     = list(type = "string"),
    confidence = list(type = "number")
  ),
  required = list("answer", "confidence"),
  additionalProperties = FALSE
)

chat_oai$send_structured(
  "Return an answer and a confidence score (0-1) about: Why is the sky blue?",
  schema
)