auto_fix: Autonomous Data Science Pipelines

In aisdk: Unified Interface for AI Model Providers

Autonomous Data Science Pipelines

Description

Self-healing runtime for R code execution. Implements a "Hypothesis-Fix-Verify" loop that feeds error messages, stack traces, and context back to an LLM for automatic error correction.

Execute R code with automatic error recovery using LLM assistance. When code fails, the error is analyzed and a fix is attempted automatically.

Usage

auto_fix(
  expr,
  model = NULL,
  max_attempts = 3,
  context = NULL,
  verbose = TRUE,
  memory = NULL
)

Arguments

expr	The R expression to execute.
model	The LLM model to use for error analysis (default: from options).
max_attempts	Maximum number of fix attempts (default: 3).
context	Optional additional context about the code's purpose.
verbose	Print progress messages (default: TRUE).
memory	Optional ProjectMemory object for learning from past fixes.

Value

The result of successful execution, or an error if all attempts fail.

Examples

## Not run: 
# Simple usage - auto-fix a data transformation
result <- auto_fix({
  df <- read.csv("data.csv")
  df %>%
    filter(value > 100) %>%
    summarize(mean = mean(value))
})

# With context for better error understanding
result <- auto_fix(
  expr = {
    model <- lm(y ~ x, data = df)
  },
  context = "Fitting a linear regression model to predict sales"
)

## End(Not run)

aisdk documentation built on May 29, 2026, 9:07 a.m.