The Most Powerful Python One-Liner in the World

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πŸ’‘ Why Is This The Most Powerful One-Liner? This one-liner demonstrates how just a single line of Python code can unlock the vast capabilities of AI, allowing you to interact with and get responses from a highly advanced model with ease, making powerful technology accessible with minimal effort.

import openai; print(openai.OpenAI(api_key="sk-...").chat.completions.create(model="gpt-4-turbo-preview", messages=[{"role": "user", "content": "2+2="}]).choices[0].message.content)
# Output: 2+2=4

This assumes you’ve installed OpenAI with pip install openai. More details here:

πŸ‘‰ How to Install OpenAI?

The one-liner imports the OpenAI class from the openai module, then immediately creates an instance of OpenAI using an API key.

Now create an OpenAI API key that you copy and paste into the previous code snippet (api_key="sk-...", replace with your API key). You can create one at the official OpenAI website here:

The code snippet then makes a request to the chat.completions.create method with specific parameters, including the model name and a list containing a single message with the role of "user" and content "2+2=". πŸ‘ˆ This is where you can put your prompt. Any prompt!

πŸ’‘ Example: For instance, you can ask it to analyze the sentiment of a certain tweet without writing a whole machine learning sentiment classification system. You can also ask it to write any code for you.

Finally, it prints the content of the first response message received from the API call.

For reference, the original multi-liner is as follows:

from openai import OpenAI
client = OpenAI(api_key="sk-...")

response =
      "role": "user",
      "content": "2+2=" # <-- Your Prompt Here

This code snippet starts by importing the OpenAI class from the openai module and then creates an instance of this class called client, initialized with a specific API key.

It uses this client instance to call the chat.completions.create method, specifying a model and a list of messages where the user asks “2+2=”.

The method returns a response object containing possible completions, and the script prints the content of the first message from these completions.

Essentially, it demonstrates how to use the OpenAI API to get a response to a simple query, showcasing interaction with AI models.

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