RAG
April 30, 2026 · View on GitHub
Articles
- Build a Retrieval Augmented Generation (RAG) App
- Building a Local RAG System for Privacy Preservation with Ollama and Weaviate
- Typical RAG Implementation Using Semantic Kernel, Kernel Memory, and Aspire in .NET
- Using Phi-3 & C# with ONNX for text and vision samples
- Introducing Phi-3: Redefining what’s possible with SLMs
- Optimizing SLM with ONNX Runtime: Phi-3 on CPU with Sidecars for App Service
- Building Smarter Apps: Integrating Phi-3 SLM with Linux App Service
- Building an Advanced RAG System With Self-Querying Retrieval
- Demystifying Retrieval Augmented Generation with .NET
- Building Intelligent Applications with Local RAG in .NET and Phi-3: A Hands-On Guide
- Bring your AI Copilots to the edge with Phi-3 and Semantic Kernel
- Building RAG with .NET Aspire and Python
Videos
Libraries
- microsoft/kernel-memory - RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns
Samples
- NikiforovAll/notebook-agent - Demonstrates how to use Semantic Kernel and Kernel Memory in a polyglot notebook environment.
- luisquintanilla/RAGDotnetAIFundamentals - This sample shows how to apply vanilla / simple RAG pattern using .NET fundamentals in the AI ecosystem