Package: LLMing
Title: Large Language Model (LLM) Tools for Psychological Text Analysis
Version: 1.2.1
Authors@R: c(
    person("Lindley", "Slipetz", email = "ddj6tu@virginia.edu",
           role = c("aut", "cre")),
    person("Teague", "Henry", email = "ycp6wm@virginia.edu",
           role = "aut"),
    person("Siqi", "Sun", email = "mgd6vc@virginia.edu",
           role = "ctb")
    )
Maintainer: Lindley Slipetz <ddj6tu@virginia.edu>
Description: A collection of large language model (LLM) text analysis methods
  designed with psychological data in mind. Currently, LLMing (aka "lemming")
  includes a text anomaly detection method based on the angle-based subspace
  approach described by Zhang, Lin, and Karim (2015) and a text generation method.
  <doi:10.1016/j.ress.2015.05.025>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: Rdpack, quanteda, stopwords, stringi, reticulate, text,
        dbscan, pracma, stats, jsonlite, quanteda, stopwords, stringi,
        utils, Matrix, text2vec
SystemRequirements: Python (>= 3.10) with packages: torch,
        transformers, pandas, numpy
RdMacros: Rdpack
URL: https://github.com/sliplr19/LLMing
BugReports: https://github.com/sliplr19/LLMing/issues
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-03-26 17:34:33 UTC; ddj6tu
Author: Lindley Slipetz [aut, cre],
  Teague Henry [aut],
  Siqi Sun [ctb]
Repository: CRAN
Date/Publication: 2026-03-27 14:20:02 UTC
Built: R 4.6.0; ; 2026-04-30 20:33:50 UTC; unix
