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pip install -U openai -q

Using the GPT-4.1 Nano model for text-to-text generation

from openai import OpenAI
from IPython.display import Markdown, display

client = OpenAI()

response = client.responses.create(
    model="gpt-4.1-nano",
    input= "Write a proper blog on getting rich."
)

Markdown(response.output_text)

Using the GPT-4.1 Mini model for image understanding

response = client.responses.create(
    model="gpt-4.1-mini",
    input=[{
        "role": "user",
        "content": [
            {"type": "input_text", "text": "Please describe the image as a philosopher would."},
            {
                "type": "input_image",
                "image_url": "https://thumbs.dreamstime.com/b/lucha-de-dos-vacas-56529466.jpg",
            },
        ],
    }],
)

print(response.output_text)

Using the GPT-4.1 (Full) model for code generation

import sys

# Request a streamed response from the model.
stream = client.responses.create(
    model="gpt-4.1",
    instructions="You are a machine learning engineer, which is an expert in creating model inference.",
    input="Create a FastAPI app for image classification",
    stream=True,
)

# Iterate over stream events and print text as soon as it's received.
for event in stream:
    # Check if the event includes a text delta.
    if hasattr(event, "delta") and event.delta:
        sys.stdout.write(event.delta)
        sys.stdout.flush()

Using the GPT-4.1 (Full) model for code generation with file inputs

import base64
from openai import OpenAI
client = OpenAI()

with open("main.py", "rb") as f:
    data = f.read()

base64_string = base64.b64encode(data).decode("utf-8")

response = client.responses.create(
    model="gpt-4.1",
    input=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_file",
                    "filename": "main.py",
                    "file_data": f"data:text/x-python;base64,{base64_string}",
                },
                {
                    "type": "input_text",
                    "text": "Enhance the code by incorporating additional features to improve the user experience.",
                },
            ],
        },
    ]
)

Markdown(response.output_text)