Building an Interactive Chatbot with Prompt Engineering using ChatGPT, .NET Core, and Azure


In today's fast-paced digital landscape, businesses are increasingly relying on chatbots to streamline customer interactions. Crafting a chatbot that can effectively understand and respond to diverse queries necessitates a fusion of natural language processing (NLP) methodologies and robust engineering techniques. This comprehensive guide will walk you through the process of harnessing the capabilities of OpenAI's ChatGPT, seamlessly integrating it with a .NET Core application, and deploying it on Microsoft Azure. By following these steps, you'll be equipped to construct a fully functional interactive chatbot tailored to meet your specific needs.

Understanding the Landscape

Before delving into the technical intricacies, it's crucial to grasp the foundational concepts underpinning our endeavor. Chatbots serve as virtual assistants capable of engaging in conversations with users, simulating human-like interactions through text or speech. Prompt engineering, a burgeoning approach within the realm of AI, involves providing tailored prompts or cues to language models like ChatGPT to elicit desired responses. This method empowers developers to shape the conversational flow and enhance the relevance and coherence of the bot's replies.


To embark on this journey, ensure you have the following prerequisites in place.

  1. Proficiency in .NET Core development.
  2. Access to an Azure subscription for deploying the application.
  3. Familiarity with REST APIs and JSON.

Step 1. Setting up Azure Cognitive Services

Our first step involves configuring Azure Cognitive Services, a suite of AI-powered tools offered by Microsoft Azure. Navigate to the Azure portal and create a new Cognitive Services resource. Opt for the "Language" category and select "Text Analytics" to leverage its robust NLP capabilities. Upon creation, make note of the endpoint URL and access key provided by Azure, as we'll utilize them later in our application.

Step 2. Integrating ChatGPT with .NET Core

With Azure Cognitive Services configured, we're ready to integrate ChatGPT into our .NET Core application. Begin by creating a new .NET Core console application using your preferred IDE. Utilize the RestSharp library, a lightweight HTTP client, to facilitate communication with the OpenAI API.

End-to-End Code

// Install RestSharp package dotnet add package RestSharp
using RestSharp;
using System;

public class ChatGPT
    private const string ApiKey = "YOUR_OPENAI_API_KEY";
    private const string BaseUrl = "";

    public string GetChatResponse(string prompt)
        var client = new RestClient(BaseUrl);
        var request = new RestRequest("completions", Method.POST);

        request.AddHeader("Authorization", $"Bearer {ApiKey}");
        request.AddHeader("Content-Type", "application/json");
        request.AddJsonBody(new { model = "text-davinci-002", prompt = prompt, max_tokens = 150 });

        var response = client.Execute(request);

        return response.Content;
class Program 
    static void Main(string[] args)
        var chatGPT = new ChatGPT();
        Console.WriteLine("Welcome to ChatGPT! Start typing your message or type 'exit' to quit.");

        while (true) 
            Console.Write("You: ");
            var input = Console.ReadLine();

            if (input.ToLower() == "exit")

            var response = chatGPT.GetChatResponse(input);
            Console.WriteLine("ChatGPT: " + response); 

Step 3. Creating the Chatbot Interface

Now, let's design a user-friendly interface for interacting with our chatbot. We'll implement a simple console-based interface within our .NET Core application.

Step 4. Deploying to Azure

Having implemented our chatbot locally, it's time to deploy it to the cloud for broader accessibility. Azure App Service provides a convenient platform for hosting .NET Core applications. Follow these steps to deploy your application.

  1. Publish your .NET Core application to Azure App Service.
  2. Configure the necessary application settings within Azure, including the endpoint URL and access key for Azure Cognitive Services.


In this comprehensive guide, we've navigated the process of building an interactive chatbot leveraging prompt engineering techniques, powered by ChatGPT, .NET Core, and Azure. By following these steps, you've gained insights into integrating cutting-edge AI models with robust development frameworks to create intelligent conversational agents. As you continue to explore the possibilities of AI-driven chatbots, remember to iterate, refine, and tailor your solution to meet the evolving needs of your users and stakeholders. Embrace the power of AI to revolutionize customer engagement and drive innovation in your business endeavors.

Happy Learning!

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