How to Integrate OpenAI GPT Models in .NET (C#)

TL;DR: Use OpenAI API keys securely, call GPT endpoints from C# using either a lightweight wrapper or HttpClient, and include the AI feature in your CI/CD pipeline using secrets and containerized deployments.

Why integrate GPT with .NET?

.NET developers can leverage GPT for chatbots, documentation automation, code assistance, and intelligent search. Enterprise apps built on .NET gain immediate NLP power when paired with GPT models.

Prerequisites

OpenAI API key (store in secrets manager)
.NET 6+ or .NET 7 SDK installed
Basic knowledge of C# and HTTP

Quick C# example (using HttpClient)

// Minimal example using HttpClient (pseudo)
              using System.Net.Http;
              using System.Text;
              using System.Text.Json;
              
              var client = new HttpClient();
              client.DefaultRequestHeaders.Add("Authorization", "Bearer YOUR_API_KEY");
              
              var input = new { model = "gpt-4o-mini", prompt = "Explain dependency injection in 3 lines", max_tokens=150 };
              var body = new StringContent(JsonSerializer.Serialize(input), Encoding.UTF8, "application/json");
              var res = await client.PostAsync("https://api.openai.com/v1/chat/completions", body);
              var text = await res.Content.ReadAsStringAsync();
              Console.WriteLine(text);

Using an OpenAI .NET client (example)

Install a trusted NuGet wrapper or call the REST API with HttpClient. Example of installation:

dotnet add package OpenAI

Secure your API keys

Never hard-code keys. Use environment variables, Azure Key Vault, AWS Secrets Manager, or GitHub Actions secrets for CI/CD.

DevOps & Deployment tips

Containerize the app (Docker). Use docker build and test locally.
Store secrets in the pipeline (GitHub Actions / Azure DevOps).
Run integration tests that mock GPT responses or use a dedicated test key with limits.
Deploy to scalable platforms (Azure App Service, AKS, or AWS ECS/EKS).

Real use cases

Examples: intelligent support assistants, automated release notes, code review helpers, content summarizers, and intelligent search.

Conclusion

Integrating GPT with .NET is straightforward and powerful when you follow security and DevOps best practices. At QllmSoft we help teams implement and operate AI features responsibly and efficiently.

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