foundry_embed: Generate Text Embeddings

In foundryR: Data Frame Workflows for 'Microsoft Foundry'

Generate Text Embeddings

Description

Generate embedding vectors for one or more text inputs using an Azure AI Foundry deployed embedding model. Returns a tibble with the input text and corresponding embedding vectors stored as a list-column.

Usage

foundry_embed(
  text,
  model = NULL,
  dimensions = NULL,
  batch_size = 100L,
  api = c("v1", "deployment"),
  api_key = NULL,
  api_version = NULL
)

Arguments

text	Character vector. The text(s) to embed.
model	Character. The deployment name of an embedding model. Defaults to the environment variable AZURE_FOUNDRY_EMBED_MODEL.
dimensions	Integer. Optional. The number of dimensions for the output embeddings. Only supported by some models (e.g., text-embedding-3).
batch_size	Integer. Number of texts to include in each request. Default: 100.
api	Character. Endpoint style. "v1" (default) sends requests to ⁠/openai/v1/embeddings⁠ with model in the JSON body. "deployment" keeps the legacy deployment-path endpoint.
api_key	Character. Optional API key override.
api_version	Character. Optional API version override.

Details

Important: The model parameter must be a deployment of an embedding model, not a chat model. Common embedding models include:

• text-embedding-ada-002

• text-embedding-3-small

• text-embedding-3-large

Chat models (GPT-4, Claude, Llama, etc.) cannot generate embeddings. If you only have chat models deployed, you'll need to deploy an embedding model in Azure AI Foundry first.

Value

A tibble with columns:

text

Character. The original input text.

embedding

List. A numeric vector containing the embedding.

n_dims

Integer. The dimensionality of the embedding.

.input_idx

Integer. Original input index.

.error

Logical. Whether the row failed.

.error_msg

Character. Error message for failed rows.

Examples

## Not run: 
# Requires a configured Azure endpoint and credentials,
# plus embedding deployments.
# Single text
foundry_embed("Hello, world!", model = "text-embedding-ada-002")

# Multiple texts
texts <- c("Data science is fun", "R is great for statistics")
foundry_embed(texts, model = "text-embedding-ada-002")

# With reduced dimensions (model-dependent)
foundry_embed("Hello", model = "text-embedding-3-small", dimensions = 256)

## End(Not run)

foundryR documentation built on Sept. 25, 2026, 1:10 a.m.