util_fetch_embeddings

Fetch embeddings (Hugging Face utility)

A lightweight toolkit for text retrieval and NLP with a consistent and
predictable API organized around four actions: fetching, reading,
processing, and searching. Functions cover the full pipeline from web
data acquisition to text processing and indexing. Multiple search
strategies are supported including regex, BM25 keyword ranking, cosine
similarity, and dictionary matching. Pipe-friendly with no heavy
dependencies and all outputs are plain data frames. Also useful as a
building block for retrieval-augmented generation pipelines and
autonomous agent workflows.

Jason Timm

textpress

A Lightweight and Versatile NLP Toolkit

util_fetch_embeddings function

<dl><dt>corpus</dt>
<dd>A data frame or data.table with a <code>text</code> column.</dd>
<dt>by</dt>
<dd>Character vector of column names that identify each text unit.</dd>
<dt>api_token</dt>
<dd>Your Hugging Face API token.</dd>
<dt>api_url</dt>
<dd>The inference endpoint URL.</dd></dl>

Arguments

Fetch embeddings (Hugging Face utility) — util_fetch_embeddings

<dl>

<dt>corpus</dt>
<dd>A data frame or data.table with a <code>text</code> column.</dd>


<dt>by</dt>
<dd>Character vector of column names that identify each text unit.</dd>


<dt>api_token</dt>
<dd>Your Hugging Face API token.</dd>


<dt>api_url</dt>
<dd>The inference endpoint URL.</dd>

</dl>

util_fetch_embeddings: Fetch embeddings (Hugging Face utility)

Description

Usage

Value

Arguments