OpenAI o1 APIの使い方

from openai import OpenAI
client = OpenAI()

prompt = """
Write a bash script that takes a matrix represented as a string with 
format '[1,2],[3,4],[5,6]' and prints the transpose in the same format.
"""

response = client.chat.completions.create(
    model="o1",
    messages=[
        {
            "role": "user", 
            "content": prompt
        }
    ]
)

print(response.choices[0].message.content)

{
  "usage": {
    "prompt_tokens": 9,  # 入力トークン
    "completion_tokens": 12,  # 出力トークン
    "total_tokens": 21,  #  入力トークンと出力トークンの合計
    "completion_tokens_details": {
      "reasoning_tokens": 0,  # Reasoningトークン
      "accepted_prediction_tokens": 0,  # モデルの最終出力に含まれたトークン
      "rejected_prediction_tokens": 0  # モデルの最終出力に含まれなかったトークン
    }
  }
}

from openai import OpenAI

client = OpenAI()

prompt = """
Instructions:
- Given the React component below, change it so that nonfiction books have red
  text. 
- Return only the code in your reply
- Do not include any additional formatting, such as markdown code blocks
- For formatting, use four space tabs, and do not allow any lines of code to 
  exceed 80 columns

const books = [
  { title: 'Dune', category: 'fiction', id: 1 },
  { title: 'Frankenstein', category: 'fiction', id: 2 },
  { title: 'Moneyball', category: 'nonfiction', id: 3 },
];

export default function BookList() {
  const listItems = books.map(book =>
    <li>
      {book.title}
    </li>
  );

  return (
    <ul>{listItems}</ul>
  );
}
"""

response = client.chat.completions.create(
    model="o1-mini",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": prompt
                },
            ],
        }
    ]
)

print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI()

prompt = """
I want to build a Python app that takes user questions and looks 
them up in a database where they are mapped to answers. If there 
is close match, it retrieves the matched answer. If there isn't, 
it asks the user to provide an answer and stores the 
question/answer pair in the database. Make a plan for the directory 
structure you'll need, then return each file in full. Only supply 
your reasoning at the beginning and end, not throughout the code.
"""

response = client.chat.completions.create(
    model="o1-preview",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": prompt
                },
            ],
        }
    ]
)

print(response.choices[0].message.content)

from openai import OpenAI
client = OpenAI()

prompt = """
What are three compounds we should consider investigating to 
advance research into new antibiotics? Why should we consider 
them?
"""

response = client.chat.completions.create(
    model="o1",
    messages=[
        {
            "role": "user", 
            "content": prompt
        }
    ]
)

print(response.choices[0].message.content)