Package 'gemini.R'

Title: Interface for 'Google Gemini' API
Description: Provides a comprehensive interface for Google Gemini API, enabling users to access and utilize Gemini Large Language Model (LLM) functionalities directly from R. This package facilitates seamless integration with Google Gemini, allowing for advanced language processing, text generation, and other AI-driven capabilities within the R environment. For more information, please visit <https://ai.google.dev/docs/gemini_api_overview>.
Authors: Jinhwan Kim [aut, cre, cph] , Maciej Nasinski [ctb]
Maintainer: Jinhwan Kim <[email protected]>
License: MIT + file LICENSE
Version: 0.10.1
Built: 2025-03-19 05:17:28 UTC
Source: https://github.com/jhk0530/gemini.R

Help Index

Add history for chating context

Description

Add history for chating context

Usage

addHistory(history, role = NULL, item = NULL)

Arguments

history

The history of chat
role

The role of chat: "user" or "model"
item

The item of chat: "prompt" or "output"

Value

The history of chat

Count Tokens for Gemini Content (Including Images)

Description

Calculates the token count for a given content, including text and image data, using the Vertex AI Gemini API.

Usage

countTokens(
  jsonkey = NULL,
  model_id = NULL,
  content = NULL,
  region = "us-central1"
)

Arguments

jsonkey

A path to JSON file containing the service account key from Vertex AI.
model_id

The ID of the Gemini model.
content

The content (text, image, or list of text/image parts) for which to count tokens.

  • For text, provide a string.

  • For images, provide a list with data (base64 encoded image) and mimeType (e.g., "image/png", "image/jpeg").

  • For multiple content parts, provide a list where each element is either a text string or an image list.

region

The Google Cloud region where your Vertex AI resources are located (default is "us-central1"). See https://cloud.google.com/vertex-ai/docs/regions for available regions.

Value

A numeric value representing the token count of the content.

Examples

## Not run: 
library(gemini.R)

# For text content
key_file <- "YOURAPIKEY.json"
model <- "2.0-flash"
token_count_text <- countTokens(
  jsonkey = key_file, 
  model_id = model, 
  content = "Hello, world!"
)
print(token_count_text)

# For image content (assuming 'image.jpg' is in your working directory)
image_data <- base64enc::base64encode("image.jpg")
image_content <- list(data = image_data, mimeType = "image/jpeg")
token_count_image <- countTokens(
  jsonkey = key_file,
  model_id = model,
  content = image_content
)
print(token_count_image)

# For multiple content parts (text and image)
content_parts <- list(
  list(text = "This is the first part."),
  list(data = image_data, mimeType = "image/jpeg"),
  list(text = "This is the last part")
)
token_count_parts <- countTokens(
  jsonkey = key_file,
  model_id = model,
  content = content_parts
)
print(token_count_parts)

## End(Not run)

Generate text from text with Gemini

Description

Generate text from text with Gemini

Usage

gemini(
  prompt,
  model = "2.0-flash",
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

prompt

The prompt to generate text from
model

The model to use. Options are "2.0-flash", "2.0-flash-lite", "2.0-pro-exp-02-05". Default is '2.0-flash'. see https://ai.google.dev/gemini-api/docs/models/gemini
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

Generated text

See Also

https://ai.google.dev/docs/gemini_api_overview#text_input

Examples

## Not run: 
library(gemini.R)
setAPI("YOUR_API_KEY")
gemini("Explain dplyr's mutate function")

## End(Not run)

Analyze audio using Gemini

Description

This function sends audio to the Gemini API and returns a text description.

Usage

gemini_audio(
  audio = NULL,
  prompt = "Describe this audio",
  model = "2.0-flash",
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

audio

Path to the audio file (default: uses a sample file). Must be an MP3.
prompt

A string describing what to do with the audio.
model

The model to use. Options are "2.0-flash", "2.0-flash-lite", "2.0-pro-exp-02-05". Default is '2.0-flash' see https://ai.google.dev/gemini-api/docs/models/gemini
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

A character vector containing the Gemini API's response.

Examples

## Not run: 
library(gemini.R)
setAPI("YOUR_API_KEY")
gemini_audio(audio = system.file("docs/reference/helloworld.mp3", package = "gemini.R"))

## End(Not run)

Analyze Audio using Gemini Vertex API

Description

This function sends audio to the Gemini API and returns a text description.

Usage

gemini_audio.vertex(
  audio = NULL,
  prompt = "Describe this audio",
  tokens = NULL,
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

audio

Path to the audio file (character string). only supports "mp3".
prompt

A prompt to guide the Gemini API's analysis (character string, defaults to "Describe this audio").
tokens

A list containing the API URL and key from token.vertex() function.
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

A character vector containing the Gemini API's description of the audio.

Multi-turn conversations (chat)

Description

Generate text from text with Gemini

Usage

gemini_chat(
  prompt,
  history = list(),
  model = "2.0-flash",
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

prompt

The prompt to generate text from
history

history object to keep track of the conversation
model

The model to use. Options are "2.0-flash", "2.0-flash-lite", "2.0-pro-exp-02-05". Default is '2.0-flash' see https://ai.google.dev/gemini-api/docs/models/gemini
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

Generated text

See Also

https://ai.google.dev/docs/gemini_api_overview#chat

Examples

## Not run: 
library(gemini.R)
setAPI("YOUR_API_KEY")

chats <- gemini_chat("Pretend you're a snowman and stay in character for each")
print(chats$outputs)

chats <- gemini_chat("What's your favorite season of the year?", chats$history)
print(chats$outputs)

chats <- gemini_chat("How do you think about summer?", chats$history)
print(chats$outputs)

## End(Not run)

Generate text from text and image with Gemini

Description

Generate text from text and image with Gemini

Usage

gemini_image(
  image = NULL,
  prompt = "Explain this image",
  model = "2.0-flash",
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234,
  type = "png"
)

Arguments

image

The image to generate text
prompt

The prompt to generate text, Default is "Explain this image"
model

The model to use. Options are "2.0-flash", "2.0-flash-lite", "2.0-pro-exp-02-05". Default is '2.0-flash' see https://ai.google.dev/gemini-api/docs/models/gemini
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
type

The type of image. Options are 'png', 'jpeg', 'webp', 'heic', 'heif'. Default is 'png'

Value

Generated text

See Also

https://ai.google.dev/docs/gemini_api_overview#text_image_input

Examples

## Not run: 
library(gemini.R)
setAPI("YOUR_API_KEY")
gemini_image(image = system.file("docs/reference/figures/image.png", package = "gemini.R"))

## End(Not run)

Generate text from text and image with Gemini Vertex API

Description

Generate text from text and image with Gemini Vertex API

Usage

gemini_image.vertex(
  image = NULL,
  prompt = "Explain this image",
  type = "png",
  tokens = NULL,
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

image

The image to generate text
prompt

A character string specifying the prompt to use with the image. Defaults to "Explain this image".
type

A character string specifying the image type ("png", "jpeg", "webp", "heic", "heif"). Defaults to "png".
tokens

A list containing the API URL and key from token.vertex() function.
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

A character string containing Gemini's description of the image.

Generate text from text with Gemini Vertex API

Description

Generate text from text with Gemini Vertex API

Usage

gemini.vertex(
  prompt = NULL,
  tokens = NULL,
  temperature = 1,
  maxOutputTokens = 8192,
  topK = 40,
  topP = 0.95,
  seed = 1234
)

Arguments

prompt

A character string containing the prompt for the Gemini model.
tokens

A list containing the API URL and key from token.vertex() function.
temperature

The temperature to use. Default is 1 value should be between 0 and 2 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
maxOutputTokens

The maximum number of tokens to generate. Default is 8192 and 100 tokens correspond to roughly 60-80 words.
topK

The top-k value to use. Default is 40 value should be between 0 and 100 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
topP

The top-p value to use. Default is 0.95 value should be between 0 and 1 see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters
seed

The seed to use. Default is 1234 value should be integer see https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters

Value

A character string containing the generated text.

See Also

https://ai.google.dev/docs/gemini_api_overview#text_input

Examples

## Not run: 
# token should be created before this. using the token.vertex() function
prompt <- "What is sachins Jersey number?"
gemini.vertex(prompt, tokens)

## End(Not run)

Generate Roxygen Documentation

Description

Generates Roxygen2 documentation for an R function based on the currently selected code.

Usage

gen_docs(prompt = NULL)

Arguments

prompt

A character string specifying additional instructions for the LLM. Defaults to a prompt requesting Roxygen2 documentation without the original code.

Value

A character string containing the generated Roxygen2 documentation.

Generates unit test code for an R function.

Description

Generates unit test code for an R function.

Usage

gen_tests(prompt = NULL)

Arguments

prompt

A character string specifying the prompt for the Gemini model. If NULL, a default prompt is used.

Value

#' A character string containing the generated unit test code.

Store API key in local environment file

Description

Saves the API key to a local .Renviron file for persistent access across R sessions

Usage

setEnv(api_key, overwrite = TRUE, install_message = TRUE)

Arguments

api_key

The API key to store
overwrite

Whether to overwrite the existing API key if already present in .Renviron (default: TRUE)
install_message

Whether to display a message about how to use the API (default: TRUE)

Value

No return value, called for side effects.

See Also

setAPI which sets the API key for the current session only

Examples

## Not run: 
setEnv("your_api_key")

## End(Not run)

Generate Gemini Access Token and Endpoint URL

Description

Generates an access token for the Gemini model and constructs the corresponding endpoint URL.

Usage

token.vertex(
  jsonkey = NULL,
  model_id = NULL,
  expTime = 3600,
  region = "us-central1"
)

Arguments

jsonkey

A path to JSON file containing the service account key from Vertex AI.
model_id

The ID of the Gemini model. This will be prepended with "gemini-".
expTime

The expiration time of the access token in seconds (default is 3600 seconds, or 1 hour).
region

The Google Cloud region where your Vertex AI resources are located (default is "us-central1"). See https://cloud.google.com/vertex-ai/docs/general/locations for available regions.

Value

A list containing:

key

The generated access token.
url

The endpoint URL for the Gemini model.

Examples

## Not run: 
library(gemini.R)
tokens <- token.vertex(jsonkey = "YOURAPIKEY.json", model_id = "1.5-flash")

# Specify a different region
tokens <- token.vertex(jsonkey = "YOURAPIKEY.json", model_id = "1.5-flash", region = "europe-west4")

## End(Not run)