build_feature_engineering_agent {LLMAgentR} | R Documentation |
Build a Feature Engineering Agent
Description
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
## Not run:
# 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)
## End(Not run)
[Package LLMAgentR version 0.3.0 Index]