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Generate Embeddings Using the Google Gemini API

Source: R/api_gemini.R
gemini_embedding.Rd

gemini-embedding-2 embeds text, images (JPEG or PNG, at most 6 per item), audio (WAV or MP3, up to 180 seconds) and video (MP4, up to 120 seconds) into one space. Media files are sent inline and must not exceed 20 MB. The model reads task instructions from the text, so .task adds a text prefix and no taskType is sent.

Usage

gemini_embedding(
  .input,
  .model = "gemini-embedding-2",
  .truncate = TRUE,
  .timeout = 120,
  .dry_run = FALSE,
  .max_tries = 3,
  .task = NULL,
  .dimensions = NULL
)

Arguments

.input

A character vector of texts to embed, a list mixing texts with img(), audio_file() and video_file() objects, or an LLMMessage object. Each list element is one row; a nested list is one fused item with a single vector.

.model

The embedding model identifier (default: "gemini-embedding-2").

.truncate

Whether to truncate inputs to fit the model's context length (default: TRUE).

.timeout

Timeout for the API request in seconds (default: 120).

.dry_run

If TRUE, perform a dry run and return the request object.

.max_tries

Maximum retry attempts for requests (default: 3).

.task

NULL (default), "query" or "document". Adds the task prefix to text; media get none.

.dimensions

Number of dimensions to return (gemini-embedding-2 accepts 128 to 3072 and renormalises the shortened vector). Default: the model's 3072.

Value

A tibble with columns input (text, or a label such as [IMG] cat.jpg) and embeddings (list of numeric vectors).