Results for "C#"

Step-by-step architectural guide to building an enterprise Retrieval-Augmented Generation (RAG) app in C# (.NET 10) combining Google Gemini embeddings with SQL Server 2025 native Vector support.

Step-by-step architectural guide to building a Retrieval-Augmented Generation (RAG) app in C# using Google Gemini API, Semantic Kernel, and Vector Data.

Learn how to build production-grade RAG systems in .NET 9 using Azure OpenAI, Semantic Kernel, and PostgreSQL pgvector with hybrid search and zero hallucinations.

Go from zero to a production-ready, tool-calling AI agent in .NET using Microsoft Semantic Kernel (Agent Framework 1.0). Learn architecture, C# code, and scaling patterns.

This guide covers the questions interviewers actually ask — from deep C# internals and async patterns to ASP.NET Core, Entity Framework, microservices, design patterns, and system design.

Create Model Context protocol(MCP) in .NET 10 C# and the test this local MCP in Visual Studio Code

Learn how to build flexible AI agents in C# using the Microsoft Agent Framework. This step-by-step tutorial shows you how to integrate multiple OpenAI models via OpenRouter to avoid vendor lock-in in your .NET applications.

Learn how to integrate DeepSeek AI in ASP.NET Core Web API using OpenRouter. Step-by-step C# example, code snippets, and free API key setup guide for .NET developers.