Build a Feature Engineering Agent — build_feature_engineering

Constructs a graph-based feature engineering agent that guides the process of: recommending, generating, executing, fixing, and explaining feature engineering code.

Arguments

model: A function that accepts a prompt and returns an LLM-generated response.
human_validation: Logical; include a manual review node before code execution.
bypass_recommended_steps: Logical; skip the LLM-based recommendation phase.
bypass_explain_code: Logical; skip final explanation step.
verbose: Logical; whether to print progress messages (default: TRUE)

Value

A callable agent function that executes feature engineering via a state graph.

Examples

if (FALSE) { # \dontrun{
# 1) Load the data
data <- read.csv("tests/testthat/test-data/churn_data.csv")

# 2) Create the feature engineering agent
feature_engineering_agent <- build_feature_engineering_agent(
  model = my_llm_wrapper,
  human_validation = FALSE,
  bypass_recommended_steps = FALSE,
  bypass_explain_code = FALSE,
  verbose = TRUE
)

# 3) Define the initial state
initial_state <- list(
  data_raw = data,
  target_variable = "Churn",
  user_instructions = "Inspect the data. Make any new features and transformations
  that you think will be useful for predicting the target variable.",
  max_retries = 3,
  retry_count = 0
)

# 4) Run the agent
final_state <- feature_engineering_agent(initial_state)
} # }