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llmclean  

LLM-Assisted Data Cleaning with Multi-Provider Support
View on CRAN: Click here


Download and install llmclean package within the R console
Install from CRAN:
install.packages("llmclean")

Install from Github:
library("remotes")
install_github("cran/llmclean")

Install by package version:
library("remotes")
install_version("llmclean", "0.1.1")



Attach the package and use:
library("llmclean")
Maintained by
Sadikul Islam
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-22
Latest Update: 2026-04-22
Description:
Detects and suggests fixes for semantic inconsistencies in data frames by calling large language models (LLMs) through a unified, provider-agnostic interface. Supported providers include 'OpenAI' ('GPT-4o', 'GPT-4o-mini'), 'Anthropic' ('Claude'), 'Google' ('Gemini'), 'Groq' (free-tier 'LLaMA' and 'Mixtral'), and local 'Ollama' models. The package identifies issues that rule-based tools cannot detect: abbreviation variants, typographic errors, case inconsistencies, and malformed values. Results are returned as tidy data frames with column, row index, detected value, issue type, suggested fix, and confidence score. An offline fallback using statistical and fuzzy-matching methods is provided for use without any API key. Interactive fix application with human review is supported via 'apply_fixes()'. Methods follow de Jonge and van der Loo (2013) <https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf> and Chaudhuri et al. (2003) <doi:10.1145/872757.872796>.
How to cite:
Sadikul Islam (2026). llmclean: LLM-Assisted Data Cleaning with Multi-Provider Support. R package version 0.1.1, https://cran.r-project.org/web/packages/llmclean. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:53), 0.1.0 (2026-04-22 15:10)
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Complete documentation for llmclean
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Full llmclean package functions and examples
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