from random import Random from typing import Dict, Any def generate_from_variables(n: int, p1: int, p2: int, company: str, frac: float) -> Dict[str, Any]: interviews = int(n * (p1/100)) offers = int(interviews * (p2/100)) accepts = int(offers * frac) question = f"{n} people apply for a job at {company}. Of the people that apply, only {p1}% receive interviews. Of those who receive interviews, {p2}% receive a job offer. Of those who receive a job offer, {frac:.2%} of the people accept the position. How many people accept the position?" answer_cot = f"The number of people that receive interviews is {n} * {p1/100} = {interviews} people\n" \ f"The number of people that receive a job offer is {interviews} * {p2/100} = {offers} people\n" \ f"The number of people that accept the position is {offers} * {frac} = {accepts} people\n" \ f"#### {accepts}" return { 'question': question, 'answer': str(accepts), 'answer_cot': answer_cot, 'answer_value': accepts, 'variables': { 'total_applicants': n, 'interview_percent': p1, 'offer_percent': p2, 'company': company, 'acceptance_fraction': frac, 'num_interviews': interviews, 'num_offers': offers, 'num_accepts': accepts } } def generate_example(rng: Random, difficulty: float = 1.0) -> Dict[str, Any]: companies = ["Microsoft", "Apple", "Amazon", "Facebook", "Netflix", "Tesla", "Google"] fractions = {"a third": 1/3, "half": 1/2, "a quarter": 1/4, "two thirds": 2/3} company = rng.choice(companies) frac = fractions[rng.choice(list(fractions.keys()))] # Generate values ensuring all divisions result in integers n = int(rng.randint(201, int(1001 * difficulty))) p1 = int(rng.randint(10, int(51 * difficulty))) p2 = int(rng.randint(10, int(51 * difficulty))) # Ensure integer results while not (n * (p1/100)).is_integer() or \ not (n * (p1/100) * (p2/100)).is_integer() or \ not (n * (p1/100) * (p2/100) * frac).is_integer(): n = int(rng.randint(201, int(1001 * difficulty))) p1 = int(rng.randint(10, int(51 * difficulty))) p2 = int(rng.randint(10, int(51 * difficulty))) result = generate_from_variables(n, p1, p2, company, frac) return { 'question': result['question'], 'answer': result['answer'], 'metadata': { 'difficulty': difficulty, 'answer_value': result['answer_value'], 'answer_cot': result['answer_cot'], 'variables': result['variables'] } } def original_example() -> Dict[str, Any]: return generate_from_variables(100, 30, 20, "Google", 1/3)