reasoning-gym/reasoning_gym/algorithmic/spell_backward.py
2025-02-16 16:27:12 +01:00

66 lines
2.1 KiB
Python

"""Spell backward task generator"""
import re
from dataclasses import dataclass
from random import Random
from typing import Any, Dict, Optional
from ..data import read_data_file
from ..factory import ProceduralDataset, register_dataset
@dataclass
class SpellBackwardConfig:
"""Configuration for spelling words backward task generation"""
min_word_len: int = 3 # Minimum word length
seed: Optional[int] = None
size: int = 500 # Virtual dataset size
def validate(self) -> None:
"""Validate configuration parameters"""
assert self.min_word_len > 0, "min_word_len must be positive"
class SpellBackwardDataset(ProceduralDataset):
"""Generates tasks to spell words backward"""
def __init__(self, config: SpellBackwardConfig):
super().__init__(config=config, seed=config.seed, size=config.size)
# Load and preprocess text
text = read_data_file("in_the_year_2889.txt")
# Extract words and clean them to contain only alphanumeric characters
self.words = [
word for word in re.findall(r"\b\w+\b", text) if word.isalnum() and len(word) >= config.min_word_len
]
def __getitem__(self, idx: int) -> dict:
"""Generate a single spell backward task"""
rng = Random(self.seed + idx)
# Select random word
word = rng.choice(self.words)
answer = word[::-1]
return {
"question": f"Spell this word backward (example: sun -> nus): {word}",
"answer": answer,
"metadata": {"word": word, "word_len": len(word)},
}
def score_answer(self, answer: Optional[str], entry: Dict[str, Any]) -> float:
reward = 0.0
expected_answer = entry["answer"]
if answer is not None:
try:
if expected_answer.lower() == answer.lower():
reward = 1.0
else:
reward = 0.05
except:
reward = 0.01
return reward
register_dataset("spell_backward", SpellBackwardDataset, SpellBackwardConfig)