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Generate text embeddings

Source: R/llm_verbs.R
embed.Rd

The embed() function allows you to embed a text via a specified provider. It routes the input to the appropriate provider-specific embedding function.

Usage

embed(
  .input,
  .provider = getOption("tidyllm_embed_default"),
  .model = NULL,
  .truncate = NULL,
  .timeout = NULL,
  .dry_run = NULL,
  .max_tries = NULL,
  .task = NULL,
  .dimensions = NULL,
  .media_columns = FALSE
)

Arguments

.input

A character vector of texts, a list mixing texts with img(), audio_file() and video_file() objects, or an LLMMessage object. Each element of a list is embedded as its own row. A nested list, such as list(list("A cat", img("cat.jpg"))), is one fused item that gets a single vector. provider_capabilities(.what = "embed_media") shows which provider embeds which media type.

.provider

A function or function call specifying the language model provider and any additional parameters. This should be a call to a provider function like openai(), ollama(), etc. You can also set a default provider function via the tidyllm_embed_default option.

.model

The embedding model to use

.truncate

Whether to truncate inputs to fit the model's context length

.timeout

Timeout for the API request in seconds

.dry_run

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

.max_tries

Maximum retry attempts for requests

.task

"query" or "document". Adds the task prefix that EmbeddingGemma 2 and gemini-embedding-2 read from the text (and sets input_type for voyage()). Media get no prefix. Leave NULL for models that take no prefix.

.dimensions

Number of dimensions to return, for providers and models that can shorten their vectors: gemini(), openrouter(), ollama(), openai() (text-embedding-3 models) and mistral() (codestral-embed). voyage() calls this argument .output_dimension. llamacpp() has no such argument, because llama-server ignores it.

.media_columns

If TRUE, add a modality and a path column after input. modality is "text", "image", "audio" or "video"; a fused item lists its parts joined by " + ", such as "text + image". path holds the file path of the media in the item (joined by " + " for several files) and is NA for text. Has no effect with .dry_run = TRUE, which returns the request. Defaults to FALSE.

Value

A tibble with the columns input and embeddings, plus modality and path when .media_columns = TRUE. The input column contains the texts sent to embed, or a label such as [IMG] cat.jpg for a media file. A fused item shows its parts joined by " + ", for example A cat + [IMG] cat.jpg. The embeddings column is a list column where each row contains an embedding vector of the sent input.

Examples

if (FALSE) { # \dontrun{
c("What is the meaning of life, the universe and everything?",
 "How much wood would a woodchuck chuck?",
 "How does the brain work?") |>
 embed(gemini)
 } # }