tidyllm (version 0.3.4)

gemini_embedding: Generate Embeddings Using the Google Gemini API

Description

Generate Embeddings Using the Google Gemini API

Usage

gemini_embedding(
  .input,
  .model = "text-embedding-004",
  .truncate = TRUE,
  .timeout = 120,
  .dry_run = FALSE,
  .max_tries = 3
)

Value

A matrix where each column corresponds to the embedding of a message in the message history.

Arguments

.input

A character vector of texts to embed or an LLMMessage object

.model

The embedding model identifier (default: "text-embedding-3-small").

.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).