% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/zzz.R
\name{set_parameters}
\alias{set_parameters}
\title{Set Processing Parameters for AI Models}
\usage{
set_parameters(n_variables = 9, id_column = 1, text_column = 2, sep = ";")
}
\arguments{
\item{n_variables}{Integer. Number of columns to extract (default is 9).
This determines the total number of columns in the final dataset.
Must be between 1 and 20.}

\item{id_column}{Integer. The column number containing the unique ID for each
observation (default is 1). Must be a positive integer.}

\item{text_column}{Integer. The column number containing the text content
to be processed (default is 2). Must be a positive integer.}

\item{sep}{Character. Separator used in API response parsing (default is ";").
Must be one of: ";" (semicolon), "," (comma), or "|" (vertical bar).}
}
\value{
Character. A confirmation message indicating the parameters have been set.
}
\description{
This function configures the parameters that will be used by AI models
to extract machine-readable variables from natural language text.
}
\details{
The function sets the expected parameters in the package's internal
environment. This affects:
\itemize{
\item Response parsing and validation
\item Column naming (Var1, Var2, ..., VarN)
\item Data structure expectations across all processing functions
\item Column identification for text content and unique IDs
\item Separator used for parsing API responses
}

The package automatically adds a unique internal ID column to each row during processing.
This internal ID is used for tracking and is removed from the final output.

The total expected columns will be n_variables:
\itemize{
\item All columns: Var1, Var2, ..., VarN
}
}
\examples{
\dontrun{
# Extract 4 columns, ID in column 1, text in column 2, semicolon separator
set_parameters(n_variables = 4, id_column = 1, text_column = 2, sep = ";")

# Extract 10 columns, ID in column 3, text in column 5, comma separator
set_parameters(n_variables = 10, id_column = 3, text_column = 5, sep = ",")

# Extract 6 columns, ID in column 2, text in column 3, vertical bar separator
set_parameters(n_variables = 6, id_column = 2, text_column = 3, sep = "|")
}

}
