Create a new Google Gemini llm_provider() instance — llm_provider_google

Creates an llm_provider() object that interacts with the Google Gemini API. Streaming is not yet supported in this implementation.

Usage

llm_provider_google_gemini(
  parameters = list(model = "gemini-1.5-flash"),
  verbose = getOption("tidyprompt.verbose", TRUE),
  url = "https://generativelanguage.googleapis.com/v1beta/models/",
  api_key = Sys.getenv("GOOGLE_AI_STUDIO_API_KEY")
)

Arguments

parameters

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

model: The name of the model to use (see: https://ai.google.dev/gemini-api/docs/models/gemini)

Additional parameters are appended to the request body; see the Google AI Studio API documentation for more information: https://ai.google.dev/gemini-api/docs/text-generation & https://github.com/google/generative-ai-docs/blob/main/site/en/gemini-api/docs/get-started/rest.ipynb

verbose

A logical indicating whether the interaction with the LLM provider should be printed to the console

url

The URL to the Google Gemini API endpoint for chat completion

api_key

The API key to use for authentication with the Google Gemini API (see: https://aistudio.google.com/app/apikey)

Value

A new llm_provider() object for use of the Google Gemini API

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()

# 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?"
} # }
# 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()

# 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?"
} # }

Create a new Google Gemini `llm_provider()` instance

Usage

Arguments

Value

See also

Examples