Run iterative refactor tasks with RALPH

#!/usr/bin/env python3 """ RALPH Loop Runner for RefactorBench. Runs iterative agent retry loops with filesystem-based memory on a SINGLE task at a time. RALPH pattern: - Agent runs, does work, exits - Work persists on the filesystem (working directory retains all changes) - Fresh agent starts, reads progress.json from the working directory, continues - Repeats until tests pass or max iterations Usage: python3 ralph runner.py --repo django refactor --task add-log-parameter-get-resolver python3 ralph runner.py --repo django refactor --task add-log-parameter-get-resolver --chains 2 --iterations 3 python3 ralph runner.py --repo django refactor --task add-log-parameter-get-resolver --verbose """ import argparse import asyncio import json import os import re import shutil import sys import time from dataclasses import dataclass from datetime import datetime from pathlib import Path from refactor agent import get task info, run test, setup workdir from notebook import ( FileSnapshot, NotebookWriter, parse stream json, compute solution diff, compute diff stats, ) import ralph prompt builder BENCH ROOT = Path( file ).parent / ".refactorbench" # --------------