hf_nearest_neighbors: Find Nearest Neighbors by Semantic Similarity

In huggingfaceR: Access 'Hugging Face' Models and Datasets

Find Nearest Neighbors by Semantic Similarity

Description

Find the k most similar texts to a query text based on embedding similarity.

Usage

hf_nearest_neighbors(
  data,
  query,
  k = 5,
  text_col = "text",
  model = hf_default_model("embed"),
  token = NULL
)

Arguments

data	A data frame with an 'embedding' column (from hf_embed_text).
query	Character string. The query text to compare against.
k	Integer. Number of nearest neighbors to return. Default: 5.
text_col	Character string. Name of text column. Default: "text".
model	Character string. Model to use for query embedding. Should match the model used for data embeddings.
token	Character string or NULL. API token for authentication.

Value

A tibble with the k nearest neighbors, sorted by similarity (descending).

Examples

## Not run: 
docs_embedded |>
  hf_nearest_neighbors("machine learning", k = 5)

## End(Not run)

huggingfaceR documentation built on Aug. 30, 2026, 1:06 a.m.