Pythonchain_of_thought.py
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import os
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import re
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from collections import Counter
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import openai
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client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
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# ── Zero-shot CoT ───────────────────────────────────────────────────
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def direct_answer(question: str) -> str:
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    response = client.chat.completions.create(
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        model="gpt-4o-mini",
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        messages=[{"role": "user", "content": question}],
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        max_tokens=50, temperature=0,
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    )
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    return response.choices[0].message.content.strip()
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def cot_answer(question: str) -> str:
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    response = client.chat.completions.create(
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        model="gpt-4o-mini",
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        messages=[{
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            "role": "user",
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            "content": f"{question}
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Let's think step by step.",
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        }],
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        max_tokens=300, temperature=0,
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    )
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    return response.choices[0].message.content.strip()
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# ── Few-shot CoT ────────────────────────────────────────────────────
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FEW_SHOT_EXAMPLES = """Q: A store has 24 apples. If 3/8 are red and the rest are green, how many are green?
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A: Let me solve step by step.
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   Red apples: 24 × (3/8) = 24 × 3 / 8 = 72 / 8 = 9
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   Green apples: 24 - 9 = 15
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   Answer: 15 green apples.
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Q: If a train travels 120km in 2 hours, how far does it travel in 5 hours?
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A: Let me solve step by step.
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   Speed: 120 / 2 = 60 km/h
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   Distance in 5 hours: 60 × 5 = 300 km
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   Answer: 300 km.
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"""
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def few_shot_cot(question: str) -> str:
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    prompt = FEW_SHOT_EXAMPLES + f"Q: {question}
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A: "
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    response = client.chat.completions.create(
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        model="gpt-4o-mini",
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        messages=[{"role": "user", "content": prompt}],
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        max_tokens=300, temperature=0,
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    )
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    return response.choices[0].message.content.strip()
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# ── Self-consistency ────────────────────────────────────────────────
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def extract_final_number(text: str) -> str | None:
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    """Extract the final numeric answer from CoT response."""
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    numbers = re.findall(r'd+(?:.d+)?', text)
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    return numbers[-1] if numbers else None
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def self_consistent_answer(question: str, n: int = 5) -> str:
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    """Sample n CoT responses and majority-vote the answer."""
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    responses = []
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    for _ in range(n):
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        response = client.chat.completions.create(
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            model="gpt-4o-mini",
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            messages=[{
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                "role": "user",
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                "content": f"{question}
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Let's think step by step.",
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            }],
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            max_tokens=300, temperature=0.7,
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        )
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        text = response.choices[0].message.content
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        answer = extract_final_number(text)
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        if answer:
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            responses.append(answer)
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    if not responses:
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        return "Unable to extract consistent answer"
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    counter = Counter(responses)
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    most_common, votes = counter.most_common(1)[0]
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    return f"{most_common} (confidence: {votes}/{n})"
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# ── Comparison ─────────────────────────────────────────────────────
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PROBLEM = "A bakery makes 48 cupcakes. They sell 3/4 of them in the morning and 1/2 of the remaining in the afternoon. How many cupcakes are left?"
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print(f"Problem: {PROBLEM}
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")
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print(f"Direct: {direct_answer(PROBLEM)}")
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print(f"Zero-shot CoT:\n{cot_answer(PROBLEM)[:200]}...")
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print(f"Few-shot CoT:\n{few_shot_cot(PROBLEM)[:200]}...")
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print(f"Self-consistent (n=3): {self_consistent_answer(PROBLEM, n=3)}")
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