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Provides provider-agnostic tools for jointly comparing and optimizing prompts, language-model providers, and generation strategies for generative artificial intelligence workflows. Candidate configurations can be evaluated using user-supplied scoring functions, cost and latency measurements, robustness perturbations, Pareto-front screening, budget and latency constraints, prompt evolution, adaptive routing, self-consistency, and text-output ensembles. The core workflow is designed to run offline with deterministic mock providers, while external model application programming interfaces can be connected through user-defined provider functions. Evolutionary search concepts are described by Goldberg (1989, ISBN:0201157675), and multi-objective optimization concepts are related to Deb, Pratap, Agarwal and Meyarivan (2002) <doi:10.1109/4235.996017>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | jsonlite |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2026-09-12 |
| DOI: | 10.32614/CRAN.package.AutoGenAI |
| Author: | Leila Marvian Mashhad [aut, cre] |
| Maintainer: | Leila Marvian Mashhad <leila.marveian at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | AutoGenAI results |
| Reference manual: | AutoGenAI.html , AutoGenAI.pdf |
| Vignettes: |
Getting Started with AutoGenAI (source, R code) |
| Package source: | AutoGenAI_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): AutoGenAI_0.1.0.tgz, r-release (x86_64): AutoGenAI_0.1.0.tgz, r-oldrel (x86_64): AutoGenAI_0.1.0.tgz |
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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.
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