OpenAI Series - Part 3: Chat with OpenAI using Python - Complete Tutorial 2026

Hello and welcome back. My name is Ravi. Let's get started. Welcome back to OpenAI series. In last video we have covered what is OpenAI and how do we generate the API key for the OpenAI and third the development IDE. Here we are using the PyCharm for the development. It's your choice whatever you want to use. You can use VS code or Jupiter notebook. It's totally the choices what we want to use it. Before we start this tutorial, what we need for it? First, Python. We recommend Python 3.11 version, but it's not mandatory. You can use whatever version you are using in your system. and the open API library. To install open API library, you require pip. PIP is a command line tool that is used to install the Python libraries. Once you have pip, then you can simply done a basic command pip install open AI. It will install all the required libraries and the packages for OpenAI. In our previous video, we have created open API key. So this is the same key that we created in the last video. If you have not watched that video, you can check it out first. This API key will be used in our application source code. This API key useful when we communicate with the open API server. Perfect. Now I'm going to open the PyCharm. So this is our PyCharm. Let me create the first class in the Python. So we will click new Python file. Let's say open AI chat. py. Let me write a very basic program. Let's say import OS then from open AI import open AI that means we are importing the library open AI and then we required one open AI API key that we mentioned earlier as well. So this open API key I keep in my environment variable so that it should be secured there nobody can see that when I will run this program this particular line will read out the environment variable from there I have written a very basic program here while loop so what I'm doing I'm always running in a infinite while loop here And then so I'm asking the input from the user. Let's say user will ask the question and open AI will answer it. So that means this program is particularly talk to the open AI server. Here you can see the client is open AI and then we are calling the chat completion functionality of the open AI. Here we select the GPT4 model from the open AI and then we are sending the prompt which we receive from the user. After that we will get the response from the open AI server. After that we are printing that message over the console. So it's really very basic program. Now let's see I will click on this run button and then you can see the program. So now it is asking us what's your input? That means let me type hi. Perfect. Now you can see we received the response from the OpenAI. Now let me open the OpenAI dashboard. [sighs] Here you can see there one request we sent to the dashboard. In the request if you will see there the eight tokens has been used. I will explain in the next video what is the tokens and how it impact the overall cost as well. Now let me change the GPD model from GPT4 to GPD4 Turbo. In my previous video I have explained all the GPD models like what is the GPT4, what is GP Turbo. If you want to know more about those models then you may check our previous video. So let me run this program again. Let me ask a question. What is GPT4 turbo? Let's say perfect. This is the response from the OpenAI. Now let me open the open AI dashboard to see the overall cost and the number of request in the portal. We have to go again inside the uses there will be three request. Yes. So there are three request and total tokens are 35. We will cover in the next video what are the concept or tokens here. So because we sent three request one from the GPD4 model and two for the GPD4 turbo we can see the category here. Absolutely. So you can see there's a one request for the GPD4 and there are two request for the GPD4 turbo. If you will see the prices here, prices are very much high compared to GPT4. Reason being GPT4 Turbo is costly model. You are basically seeing why less amount because we only send three request. Just think when we send millions of request then this cost will be very high. So we have to decide I mean which model we should use and what are their purpose. That's the reason I asked to you know the check our previous video. I have explained all these models in details and which one is relevant to us and which one we should use in our application. That's it for today. We have covered like how do we use the chat GPT open AAI models in our Python program. Now we can chat and can build our application accordingly.