Package: doclingr
Title: Document Intelligence via 'Docling'
Version: 0.1.0
Authors@R: c(
    person("Andre", "Leite", email = "leite@castlab.org", role = c("aut", "cre")),
    person("Marcos", "Wasilew", email = "marcos.wasilew@gmail.com", role = "aut"),
    person("Hugo", "Vasconcelos", email = "hugo.vasconcelos@ufpe.br", role = "aut"),
    person("Carlos", "Amorim", email = "carlos.agaf@ufpe.br", role = "aut"),
    person("Diogo", "Bezerra", email = "diogo.bezerra@ufpe.br", role = "aut"))
Description: An interface to 'Docling', a document-understanding
        library that converts 'PDF', 'DOCX', 'PPTX', 'HTML' and image
        documents into structured, AI-ready data. The package wraps the
        'Docling' 'Python' package through 'reticulate' to extract
        layout-aware text, tables and metadata, export to 'Markdown' or
        'JSON', and split documents into context-rich chunks suitable
        for retrieval-augmented generation (RAG) and embedding
        pipelines.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 8.0.0
URL: https://github.com/StrategicProjects/doclingr,
        https://strategicprojects.github.io/doclingr/
BugReports: https://github.com/StrategicProjects/doclingr/issues
SystemRequirements: Python (>= 3.9), docling (>= 2.20.0; tested with
        2.107.0)
Imports: reticulate (>= 1.34.0), cli, rlang, stats, tibble
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/pak/sysreqs: libpng-dev python3
Repository: https://strategicprojects.r-universe.dev
Date/Publication: 2026-07-10 20:32:53 UTC
RemoteUrl: https://github.com/strategicprojects/doclingr
RemoteRef: HEAD
RemoteSha: 165fcb630ae6f65baa8b9ec13f29095b657b8a68
NeedsCompilation: no
Packaged: 2026-07-11 07:38:53 UTC; root
Author: Andre Leite [aut, cre],
  Marcos Wasilew [aut],
  Hugo Vasconcelos [aut],
  Carlos Amorim [aut],
  Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>