                        Changes in version 1.1.2                        

Fetch

  - fetch_urls() and its DuckDuckGo scraping implementation have been
    removed.
  - fetch_rss() adds publisher-supported RSS and Atom discovery. It
    returns a flat table of article URLs and feed-supplied metadata that
    can be filtered before the selected URLs are passed to read_urls().
  - fetch_rss() assigns stable doc_id values. Passing its result table
    directly to read_urls() preserves discovery metadata in the returned
    meta table.
  - rss_politics adds a verified collection of 67 active, non-government
    US politics feeds from 61 sources. The exported catalog and its
    canonical CSV cover general political news, Congress, elections,
    polling, public opinion, and state politics; it is available
    directly as textpress::rss_politics.
  - rss_local_rags adds a pinned Local Rags RSS snapshot with the shared
    feed fields plus Census division, state, county, five-character FIPS
    geography, 2023 Rural-Urban Continuum Codes, and metro status. The
    local catalog omits the politics-specific category and source_type
    fields. Detailed discovery and 3DLNews provenance remain in the
    source repository.
  - fetch_wiki_refs() now always returns one flat table for single or
    multiple Wikipedia URLs, allowing its results to pass directly to
    read_urls().
  - Wikipedia requests now identify textpress with a package User-Agent.

                 Changes in version 1.1.1 (2026-03-17)                  

Documentation

  - Six vignettes added covering the full pipeline: web data, Wikipedia
    data, regex search, dictionary search, semantic search (RAG), and
    basic NLP processing.
  - Basic NLP vignette walks through nlp_split_sentences(),
    nlp_tokenize_text() (word and Biber methods), and nlp_cast_tokens()
    stepwise and as a single pipe.
  - README revamped: tighter intro, API map, RAG/agent positioning,
    vignette links.

Changes

  - util_fetch_embeddings() re-added for embedding generation via
    Hugging Face inference endpoints (reversed 1.1.0 removal; now calls
    the HF inference API rather than loading models locally).
  - nlp_cast_tokens() documented and surfaced -- flattens the token list
    from nlp_tokenize_text() into a long-format data frame with optional
    character spans.
  - Suggests trimmed: ellmer and unused packages removed.

                 Changes in version 1.1.0 (2026-02-23)                  

API and naming

  - Package is now organized around a four-stage pipeline: Fetch → Read
    → Process → Search. All functions use a consistent verb_noun
    pattern.
  - Acquire: fetch_urls() (from web search), fetch_wiki_urls(),
    fetch_wiki_refs() — return URLs or metadata, not full text.
  - Ingest: read_urls() — read content from URLs into R (replaces
    web_scrape_urls).
  - Process: nlp_split_*, nlp_tokenize_text(), nlp_index_tokens() (and
    nlp_roll_chunks() for rolling windows).
  - Search: Four retrieval options — search_regex() (regex/KWIC),
    search_index() (BM25), search_vector() (cosine over your own
    embeddings), search_dict() (dictionary match; replaces
    ner_extract_entities).
  - Common parameters standardized: corpus (replaces tif), by (replaces
    text_hierarchy).

Removed

  - In-package embedding generation (e.g. Hugging Face API). Use your
    own embedding pipeline and pass your embedding matrix as the
    \code{embeddings} argument to \code{search_vector()}.
  - Legacy names: web_search, wiki_search, wiki_find_references,
    web_scrape_urls, ner_extract_entities, sem_nearest_neighbors /
    sem_search_corpus (replaced by search_vector and search_regex).

Docs

  - README revamped around the API map and a single “golden path”
    workflow.
  - DESCRIPTION and package help updated for the four-stage pipeline;
    version set to 1.1.0.

                 Changes in version 1.0.0 (2024-10-14)                  

  - Initial release: URL fetching, URL content reading, NLP processing
    (split, tokenize, index), and corpus/search utilities.
