Generate Embeddings Using OpenAI API on Azure

Generate Embeddings Using OpenAI API on Azure

Usage

azure_openai_embedding(
  .input,
  .deployment = "text-embedding-3-small",
  .endpoint_url = Sys.getenv("AZURE_ENDPOINT_URL"),
  .api_version = "2023-05-15",
  .truncate = TRUE,
  .timeout = 120,
  .dry_run = FALSE,
  .max_tries = 3
)

Arguments

.input

Acharacter vector of texts to embed or an LLMMesssageobject

.deployment

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

.endpoint_url

Base URL for the API (default: Sys.getenv("AZURE_ENDPOINT_URL")).

.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).

Value

A tibble with two columns: input and embeddings. The input column contains the texts sent to embed, and the embeddings column is a list column where each row contains an embedding vector of the sent input.