LLMAgentR (version 0.2.2)

build_visualization_agent: Build Visualization Agent

Description

Creates a data visualization agent with configurable workflow steps.

Value

A function that takes state and returns visualization results

Arguments

model

The AI model function to use for code generation

human_validation

Whether to include human validation step (default: FALSE)

bypass_recommended_steps

Skip recommendation step (default: FALSE)

bypass_explain_code

Skip explanation step (default: FALSE)

function_name

Name for generated visualization function (default: "data_visualization")

verbose

Whether to print progress messages (default: TRUE)

Examples

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

# 2) Create the visualization agent
visualization_agent <- build_visualization_agent(
  model = my_llm_wrapper,
  human_validation = FALSE,
  bypass_recommended_steps = FALSE,
  bypass_explain_code = FALSE,
  verbose = FALSE
)

# 3) Define the initial state
initial_state <- list(
  data_raw = data,
  target_variable = "Churn",
  user_instructions = "Create a clean and visually appealing box plot to show
  the distribution of Monthly Charges across Churn categories.
  Use distinct colors for each Churn group,
  add clear axis labels, a legend, and a meaningful title.",
  max_retries = 3,
  retry_count = 0
)

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