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Create a new OpenAI LLM provider

Source: R/llm_providers.R
llm_provider_openai.Rd

This function creates a new llm_provider object that interacts with the Open AI API. Supports both the Chat Completions API (/v1/chat/completions) and the Responses API (/v1/responses).

Usage

llm_provider_openai(
  parameters = list(model = "gpt-4o-mini", stream = getOption("tidyprompt.stream", TRUE)),
  verbose = getOption("tidyprompt.verbose", TRUE),
  url = "https://api.openai.com/v1/responses",
  api_key = Sys.getenv("OPENAI_API_KEY")
)

Arguments

parameters

A named list of parameters. Currently the following parameters are required:

  • model: The name of the model to use

  • api_key: The API key to use for authentication with the OpenAI API. This should be a project API key (not a user API key)

  • url: The URL to the OpenAI API (may also be an alternative endpoint that provides a similar API.)

  • stream: A logical indicating whether the API should stream responses

Additional parameters are appended to the request body; see the OpenAI API documentation for more information: https://platform.openai.com/docs/api-reference/chat

verbose

A logical indicating whether the interaction with the LLM provider should be printed to the console. Default is TRUE.

url

The URL to the OpenAI API endpoint for chat completion (typically: "https://api.openai.com/v1/chat/completions" or "https://api.openai.com/v1/responses"; both the Chat Completions API and the Responses API are supported; the Responses API is more modern)

api_key

The API key to use for authentication with the OpenAI API

Value

A new llm_provider object for use of the OpenAI API

See also

Other llm_provider: llm_provider-class, llm_provider_ellmer(), llm_provider_google_gemini(), llm_provider_groq(), llm_provider_mistral(), llm_provider_ollama(), llm_provider_openrouter(), llm_provider_xai()

Examples

# Various providers:
ollama <- llm_provider_ollama()
openai <- llm_provider_openai()
openrouter <- llm_provider_openrouter()
mistral <- llm_provider_mistral()
groq <- llm_provider_groq()
xai <- llm_provider_xai()
gemini <- llm_provider_google_gemini()

# From an `ellmer::chat()` (e.g., `ellmer::chat_openai()`, ...):
if (FALSE) { # \dontrun{
ellmer <- llm_provider_ellmer(ellmer::chat_openai())
} # }

# Initialize with settings:
ollama <- llm_provider_ollama(
  parameters = list(
    model = "llama3.2:3b",
    stream = TRUE
  ),
  verbose = TRUE,
  url = "http://localhost:11434/api/chat"
)

# Change settings:
ollama$verbose <- FALSE
ollama$parameters$stream <- FALSE
ollama$parameters$model <- "llama3.1:8b"

if (FALSE) { # \dontrun{
# Try a simple chat message with '$complete_chat()':
response <- ollama$complete_chat("Hi!")
response
# $role
# [1] "assistant"
#
# $content
# [1] "How's it going? Is there something I can help you with or would you like
# to chat?"
#
# $http
# Response [http://localhost:11434/api/chat]
# Date: 2024-11-18 14:21
# Status: 200
# Content-Type: application/json; charset=utf-8
# Size: 375 B

# Use with send_prompt():
"Hi" |>
  send_prompt(ollama)
# [1] "How's your day going so far? Is there something I can help you with or
# would you like to chat?"
} # }