embed_google_vertex: Embed using Google Vertex API platform

In ragnar: Retrieval-Augmented Generation (RAG) Workflows

Embed using Google Vertex API platform

Description

Embed using Google Vertex API platform

Usage

embed_google_gemini(
  x,
  model = "gemini-embedding-001",
  base_url = "https://generativelanguage.googleapis.com/v1beta",
  api_key = get_envvar("GEMINI_API_KEY"),
  dims = NULL,
  task_type = "RETRIEVAL_QUERY",
  batch_size = 20L
)

embed_google_vertex(
  x,
  model,
  location,
  project_id,
  task_type = "RETRIEVAL_QUERY"
)

Arguments

x	x can be: A character vector, in which case a matrix of embeddings is returned. A data frame with a column named text, in which case the dataframe is returned with an additional column named embedding. Missing or NULL, in which case a function is returned that can be called to get embeddings. This is a convenient way to partial in additional arguments like model, and is the most convenient way to produce a function that can be passed to the embed argument of ragnar_store_create().
model	Character specifying the embedding model. See supported models in Text embeddings API
base_url	string, url where the service is available.
api_key	resolved using env var GEMINI_API_KEY
dims	An integer, can be used to truncate the embedding to a specific size.
task_type	Used to convey intended downstream application to help the model produce better embeddings. If left blank, the default used is "RETRIEVAL_QUERY". "RETRIEVAL_QUERY" "RETRIEVAL_DOCUMENT" "SEMANTIC_SIMILARITY" "CLASSIFICATION" "CLUSTERING" "QUESTION_ANSWERING" "FACT_VERIFICATION" "CODE_RETRIEVAL_QUERY" For more information about task types, see Choose an embeddings task type.
batch_size	split x into batches when embedding. Integer, limit of strings to include in a single request.
location	Location, e.g. us-east1, me-central1, africa-south1 or global.
project_id	Project ID.

Functions

• embed_google_gemini(): Use the Gemini API to create embeddings.

Examples

embed_google_gemini("hello world")

## Not run: 
embed_google_vertex(
 "hello world",
 model="gemini-embedding-001",
 project = "<your-project-id>",
 location = "us-central1"
)

## End(Not run)

ragnar documentation built on Sept. 11, 2026, 1:06 a.m.