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Initial CRAN submission.
Deciders: decider_typesafe(),
decider_openai(), decider_foundry(),
decider_openrouter() and
decider_systemone().
Questions: question_noul(),
question_choice() and
question_score().
decide() calls one model for many inputs. It returns
a tibble in the tidymodels style, with one row for each input in input
order. A failed call keeps its row, with NA answers and the
reason in .error.
Setups: decision_setup(), write_setup()
and read_setup() keep the question, the descriptions, the
references and the calibrator in one JSON file.
Scoring: score_setup() scores a setup on labeled
rows. evaluate_once() runs the one-time test.
Six vignettes: getting started, choosing a model, open models, grading with a rubric, images, and the industrial image inspection case study.
Four datasets: ohio_injuries,
ohio_recalls, textiles and
rubric_answers.
An agent skill, in
system.file("skills", "decisions", package = "decisions").
Requirements: R 4.3.0 or newer (for @ on S7
objects), httr2 1.2.0 or newer, and rlang 1.3.0 or newer. rlang 1.3.0
changed the values of rlang::hash(), and the
path files, the run hash and the calibrator hash of a setup
use it. With an older rlang, a path file or a setup from a
newer rlang does not match.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.