Generate embeddings for a single text — hf_embed

High-level function to generate embeddings for a single text string. This function handles the entire process from request creation to response processing.

Usage

hf_embed_text(
  text,
  endpoint_url,
  key_name,
  ...,
  parameters = list(),
  tidy = TRUE,
  max_retries = 5,
  timeout = 120,
  validate = FALSE,
  engine = getOption("EndpointR.hf_engine", "auto")
)

Arguments

text: Character string to get embeddings for
endpoint_url: The URL of the Hugging Face Inference API endpoint
key_name: Name of the environment variable containing the API key
...: ellipsis sent to hf_perform_request, which forwards to httr2::req_perform
parameters: Advanced usage: parameters to pass to the API endpoint. On TEI endpoints these are added to the top level of the request body.
tidy: Whether to attempt to tidy the response or not
max_retries: Maximum number of retry attempts for failed requests
timeout: Request timeout in seconds
validate: Whether to validate the endpoint before creating the request
engine: The endpoint's inference engine: "auto" (default) detects it with a call to the endpoint's /info route, "tei" for Text Embeddings Inference, "toolkit" for the default Hugging Face Inference Toolkit. Set the default for a session with options(EndpointR.hf_engine = "tei").

Value

A tibble containing the embedding vectors

Details

The text is sent as a batch of one, in the request format for the endpoint's inference engine (see the engine argument).

Examples

if (FALSE) { # \dontrun{
  # Generate embeddings using API key from environment
  embeddings <- hf_embed_text(
    text = "This is a sample text to embed",
    endpoint_url = "https://my-endpoint.huggingface.cloud",
    key_name = "HF_API_KEY"
  )
} # }