Ditch Vanilla Chain Of Thought

import instructor
from openai import OpenAI
from pydantic import BaseModel

client = instructor.from_openai(OpenAI())


class Reasoning(BaseModel):
    chain_of_thought: str


class Response(BaseModel):
    correct_answer: str


def generate_reasoning(query: str):
    return client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": f"""
                <user query>
                {query}
                </user query>

                Let's first understand the problem,
                extract relevant variables and their
                corresponding numerals, and make a
                complete plan. Then, let's carry out
                the plan, calculate intermediate
                variables (pay attention to correct
                numerical calculation and commonsense),
                solve the problem step by step, and
                show the answer.
                """,
            },
        ],
        response_model=Reasoning,
        model="gpt-4o",
    )


def extract_answer(query: str, reasoning: Reasoning):
    return client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": f"""
                <user query>
                    {query}
                </user query>

                Let's first understand the problem,
                extract relevant variables and their
                corresponding numerals, and make a
                complete plan. Then, let's carry out
                the plan, calculate intermediate
                variables (pay attention to correct
                numerical calculation and commonsense),
                solve the problem step by step, and
                show the answer.

                <reasoning>
                {reasoning.chain_of_thought}
                </reasoning>

                Therefore the answer (arabic numerals) is
                """,
            }
        ],
        model="gpt-4o",
        response_model=Response,
    )


if __name__ == "__main__":
    query = (
        "In a dance class of 20 students, 20% enrolled "
        "in contemporary dance, 25% of the remaining "
        "enrolled in jazz dance and the rest enrolled "
        "in hip-hop dance. What percentage of the entire "
        "students enrolled in hip-hop dance?"
    )

    reasoning = generate_reasoning(query)
    print(reasoning.model_dump_json(indent=2))
    """
    {
    "chain_of_thought": "Let's first break down the
    problem:\n\n1. Total number of students = 20\n2.
    Percentage enrolled in contemporary dance = 20%\n\n
    Step-by-Step Plan:\n1. Calculate the number of
    students enrolled in contemporary dance.\n2.
    Calculate the remaining students after contemporary
    dance enrollment.\n3. Calculate the percentage and
    number of students from the remaining who enrolled in
    jazz dance.\n4. Determine the remaining students who
    enrolled in hip-hop dance.\n5. Finally, calculate the
    percentage of the entire students who enrolled in
    hip-hop dance.\n\nLet's carry out the plan:\n\n1.
    Number of students enrolled in contemporary dance =
    20% of 20 = (20/100) * 20 = 4\n2. Remaining students
    after contemporary = 20 - 4 = 16\n3. Percentage of
    remaining students enrolled in jazz dance = 25%\n
    Number of students enrolled in jazz dance = 25% of 16
    = (25/100) * 16 = 4\n4. Remaining students after
    contemporary and jazz = 16 - 4 = 12\n5. The number of
    students enrolled in hip-hop dance = 12\n6.
    Percentage of entire students enrolled in hip-hop =
    (Number of hip-hop students / Total students) *
    100\n   Percentage = (12 / 20) * 100 = 60%\n\nThus,
    60% of the entire students enrolled in hip-hop dance."
    }
    """

    response = extract_answer(query, reasoning)
    print(response.model_dump_json(indent=2))
    """
    {
      "correct_answer": "60"
    }
    """