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Generate Embeddings Using the OpenRouter API

Source: R/api_openrouter.R
openrouter_embedding.Rd

Sends text to an embedding model accessible via OpenRouter and returns embedding vectors. Note that embedding models are not listed in list_models(openrouter()) — specify the model ID directly. Known supported models include "openai/text-embedding-3-small", "openai/text-embedding-3-large", and "mistralai/mistral-embed".

Images, audio and video work with multimodal embedding models such as "google/gemini-embedding-2"; "voyageai/voyage-multimodal-3.5" and "nvidia/llama-nemotron-embed-vl-1b-v2:free" take text and images only. https://openrouter.ai/api/v1/embeddings/models lists the input types per model.

Usage

openrouter_embedding(
  .input,
  .model = "openai/text-embedding-3-small",
  .timeout = 120,
  .dry_run = FALSE,
  .max_tries = 3,
  .task = NULL,
  .dimensions = NULL
)

Arguments

.input

An LLMMessage object, a character vector of texts, or a list mixing texts with img(), audio_file() and video_file() objects (a nested list is one fused item).

.model

The embedding model ID (default: "openai/text-embedding-3-small").

.timeout

Request timeout in seconds (default: 120).

.dry_run

If TRUE, returns the request object without executing it (default: FALSE).

.max_tries

Maximum retries (default: 3).

.task

NULL (default), "query" or "document". Adds the task prefix that gemini-embedding-2 reads from the text; media get none. Leave NULL for other models.

.dimensions

Number of dimensions to return, for models that can shorten their vectors (default: the model's own size).

Value

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