script_id: day_008_chain_of_thought_part2/problem_decomposition

def decompose_problem(complex_problem: str) -> str:
    """Break complex problems into sub-problems."""
    prompt = f"""I'll solve this complex problem by breaking it into smaller parts.

Problem: {complex_problem}

Let me decompose this:
1. What are the sub-problems I need to solve?
2. What order should I solve them in?
3. Let me solve each sub-problem:

Decomposition:"""

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": prompt}],
        temperature=0
    )
    return response.choices[0].message.content

# script_id: day_008_chain_of_thought_part2/verify_and_correct
def cot_with_verification(problem: str) -> str:
    """Solve with built-in verification step."""
    prompt = f"""{problem}

Please:
1. Solve this step by step
2. State your answer
3. Verify your answer by checking if it satisfies all conditions
4. If verification fails, correct your answer

Solution:"""

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": prompt}],
        temperature=0
    )
    return response.choices[0].message.content

# Example
problem = """
A store offers 20% off, then an additional 10% off the reduced price.
If the original price is $100, what is the final price?
"""

print(cot_with_verification(problem))

# script_id: day_008_chain_of_thought_part2/work_backwards
def reverse_cot(goal: str, starting_point: str) -> str:
    """Reason backwards from goal to start."""
    prompt = f"""Let's work backwards from the goal to figure out the solution.

Goal: {goal}
Starting Point: {starting_point}

Working backwards:
- What's the last step before reaching the goal?
- What comes before that?
- Continue until we reach the starting point
- Now let's trace the path forward

Reasoning:"""

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": prompt}],
        temperature=0
    )
    return response.choices[0].message.content

# script_id: day_008_chain_of_thought_part2/cot_with_extraction
import re
from openai import OpenAI

client = OpenAI()

def cot_with_extraction(problem: str) -> dict:
    """Get both reasoning and clean final answer."""

    # Step 1: Get CoT response
    cot_response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {
                "role": "user",
                "content": f"{problem}\n\nThink step by step, then end with 'FINAL ANSWER: [your answer]'"
            }
        ],
        temperature=0
    )

    full_response = cot_response.choices[0].message.content

    # Step 2: Extract the final answer
    match = re.search(r"FINAL ANSWER:\s*(.+?)(?:\n|$)", full_response, re.IGNORECASE)
    final_answer = match.group(1).strip() if match else None

    return {
        "reasoning": full_response,
        "answer": final_answer
    }

# Usage
result = cot_with_extraction("What is 15% of 80?")
print(f"Answer: {result['answer']}")  # Quick access to answer
print(f"\nFull reasoning:\n{result['reasoning']}")  # For debugging/logging