Sreenivasa Reddy Thotli

 Rate limiting can be implemented by tracking the number of API calls made and adding delays if necessary. Here's an example: using System; using System.Net.Http; using System.Text; using System.Threading; using System.Threading.Tasks; using Newtonsoft.Json; namespace ChatGPTExample {     class Program     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         private static int requestCount = 0;         private static readonly int requestLimit = 60; // Example limit         private static readonly TimeSpan timeWindow = TimeSpan.FromMinutes(1);         private static DateTime windowStart = DateTime.UtcNow;         static async Task Main(string[] args)         {             string prompt = "Explain the significance of machine learning in modern technology.";             var response = await GetChatGPTResponseWithRateLimiting(prompt);       

  Here's a step-by-step guide to create a basic chatbot using ChatGPT in a C# WinForms application: Set Up the Project : Create a new C# WinForms App in Visual Studio. Install System.Net.Http and Newtonsoft.Json via NuGet Package Manager. Design the Form : Add a TextBox for user input ( txtUserInput ). Add a Button to send the message ( btnSend ). Add a TextBox for displaying the chat conversation ( txtChat ), set its Multiline property to True . Code Example : using System; using System.Net.Http; using System.Text; using System.Threading.Tasks; using System.Windows.Forms; using Newtonsoft.Json; namespace ChatGPTWinForms {     public partial class Form1 : Form     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         public Form1()         {             InitializeComponent();         }         private async void btnSend_Click(object sender, E

 Error handling can be done using try-catch blocks and checking the HTTP response status. Here's an example: public static async Task<string> GetChatGPTResponse(string prompt) {     using (var httpClient = new HttpClient())     {         httpClient.DefaultRequestHeaders.Add("Authorization", $"Bearer {apiKey}");         var requestBody = new         {             model = "text-davinci-003",             prompt = prompt,             max_tokens = 150         };         var content = new StringContent(JsonConvert.SerializeObject(requestBody), Encoding.UTF8, "application/json");         try         {             var response = await httpClient.PostAsync(endpoint, content);             if (!response.IsSuccessStatusCode)             {                 var errorResponse = await response.Content.ReadAsStringAsync();                 throw new Exception($"API call failed with status code: {response.StatusCode}. Response: {errorResponse}");

  To call OpenAI's ChatGPT API from a C# application, you need to make HTTP requests using HttpClient . Here's an example of how to do this: Set Up the Project : Create a new C# Console Application in Visual Studio. Install System.Net.Http and Newtonsoft.Json via NuGet Package Manager. Sample code  using System; using System.Net.Http; using System.Text; using System.Threading.Tasks; using Newtonsoft.Json; namespace ChatGPTExample {     class Program     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         static async Task Main(string[] args)         {             string prompt = "Explain the significance of machine learning in modern technology.";             var response = await GetChatGPTResponse(prompt);             Console.WriteLine(response);         }         public static async Task<string> GetChatGPTResponse(string p

  This example fetches data from a URL asynchronously without blocking the main thread, demonstrating the use of async and await . By providing detailed Q&A like these on your blog, you can offer valuable solutions to your readers, helping them tackle complex SQL and C# challenges effectively. using System; using System.Net.Http; using System.Threading.Tasks; class Program {     static async Task Main(string[] args)     {         string url = "https://api.github.com/repos/dotnet/roslyn";         string result = await FetchDataAsync(url);         Console.WriteLine(result);     }     public static async Task<string> FetchDataAsync(string url)     {         using (HttpClient client = new HttpClient())         {             client.DefaultRequestHeaders.UserAgent.TryParseAdd("request");             HttpResponseMessage response = await client.GetAsync(url);             response.EnsureSuccessStatusCode();             string responseBody = await response.Content.

  Implementing dependency injection in a .NET Core console application involves setting up a ServiceCollection , configuring services, and building a service provider. Example: using Microsoft.Extensions.DependencyInjection; using System; namespace ConsoleAppDI { public interface IGreetingService { void Greet(string name); } public class GreetingService : IGreetingService { public void Greet(string name) { Console.WriteLine($"Hello, {name}!"); } } class Program { static void Main(string[] args) { // Setup DI var serviceCollection = new ServiceCollection(); ConfigureServices(serviceCollection); var serviceProvider = serviceCollection.BuildServiceProvider(); // Get service and use it var greeter = serviceProvider.GetService<IGreetingService>(); greeter.Greet("World"); } pri

  Deadlocks occur when two or more sessions permanently block each other. To handle and prevent deadlocks: Identify Deadlocks : Use the SQL Server error log or Extended Events to capture deadlock information. Enable trace flags 1204 and 1222 for detailed deadlock information. Deadlock Prevention : Ensure consistent access order for resources in your transactions. Keep transactions short and minimize lock duration. Use lower isolation levels if appropriate (e.g., READ COMMITTED instead of SERIALIZABLE ). Retry Logic : Implement retry logic in your application to handle deadlock exceptions gracefully. Use TRY...CATCH in T-SQL to handle deadlock errors.