Using an **API (Application Programming Interface)** to interact with ChatGPT allows developers to programmatically integrate ChatGPT's capabilities into their applications, products, or services.
## How to use ChatGPT API in Python?
You can use the following code in Python to interact with ChatGPT via API:
``` python
from openai import OpenAI

client = OpenAI(
  api_key="your_api_key",
)


prompt = "your_prompt"


def get_completion(prompt, model="gpt-3.5-turbo"):

    messages = [{"role": "user", "content": prompt}]

    response = client.chat.completions.create(

    model=model,

    messages=messages,

    temperature=0.7,

    )

    return response.choices[0].message.content

response = get_completion(prompt)

print(response)
```

Now, let's look at all the steps in more detail!
## Accessing ChatGPT via API
To access ChatGPT from your local server using Python, you have to:
1. Install `openai` package using `pip install openai`;
2. Get your secret API key and specify `api_key` argument of the `OpenAI` class constructor. 

You can generate your personal secret API key via the following <a 
href="https://platform.openai.com/account/api-keys"
target="_blank"
style="color: #ff8a00; font-weight: 600; text-decoration: none;"
onmouseover="this.style.color='#ff0000'"
onmouseout="this.style.color='#d27204'">Link</a>.    
After following the link, click on the following button:


Now, you can use this API key to access ChatGPT!

## Making requests
To make requests, follow these steps:

1. Create a string variable containing your request (referred to as the `prompt` variable in the code above);
2. Use `get_completion()` function to generate response. You can specify another `model` argument of this function and use another `temperature` parameter inside the function;
3. Print the response.
## Extraction of the necessary information from ChatGPT response
The response (`response` variable) received at the previous stage contains unnecessary metadata. To get a specific answer to the query, you need to use the following construction:   
`response.choices[0].message.content`.    

As a result, you can seamlessly **incorporate ChatGPT functionality into your projects** with just a few lines of code and an API key, spanning from straightforward chatbots to intricate recommendation systems and virtual consultants.

Celebrate the world of conversational AI with our 'Intro to ChatGPT' course. Dive into the fundamentals of AI-driven chatbots, understand how ChatGPT works, and explore its exciting possibilities. Join us on a journey into the future of human-AI interaction!

Now we will provide a comprehensive overview of ChatGPT, covering its core principles, user interface, API integration possibilities, and important limitations. You'll gain a deep understanding of what ChatGPT is and how it can be utilized.

Let's delve into strategies for designing effective prompts or queries to interact with the model, exploring the critical aspect of crafting clear, context-aware prompts that maximize the model's potential for providing accurate and relevant responses.

Now we will focuse on techniques and strategies for presenting the responses generated by ChatGPT in an organized and visually appealing manner.

Introduction to Chat GPT

Interaction with ChatGPT: API

How to use ChatGPT API in Python?

Accessing ChatGPT via API

Making requests

Extraction of the necessary information from ChatGPT response