NuGet package designed to make LLMs, RAG, and Agents first-class citizens in .NET

A sample Chatbot in C# using Microsoft Agent Framework

A lightweight implementation of Kernel Memory as a Service

An example that shows how to use Semantic Kernel and Kernel Memory to work with embeddings in a .NET application using SQL Server as Vector Database.

Typical RAG implementation using Semantic Kernel, Semantic Memory and Aspire

Kernel Memory. A sample project demonstrating AI-powered semantic search capabilities tailored for e-commerce websites, leveraging RAG (Retrieval-Augmented Generation) architecture

A service for automating document ingestion for Semantic Kernel's KernelMemory service

Powershell script to view kernel memory pool information

Materials for a workshop on Semantic Kernel, Kernel Memory, and Microsoft Extensions AI

Demonstrates how to use Semantic Kernel and Kernel Memory in a polyglot notebook environment.

SpotDocAI is a full-stack proof-of-concept platform for scalable document ingestion, AI-based semantic search, and natural language question answering. Users can upload collections of documents (ZIPs), which are processed asynchronously, indexed, and queried with context-aware responses, complete with source citations.

semantic-kernel Proof of Concept

AI Chatbot with Ollama & Kernel Memory

Windows terminal performance monitor showing CPU, per-core usage, deep memory (commit/kernel paged/nonpaged), and system counters. Run as admin.

A Semantic kernel Plugin for microsoft/kernel-memory based from https://github.com/matthewbolanos/todo-ai-plugin

A production-ready Retrieval-Augmented Generation (RAG) application built with .NET 10, featuring advanced document processing, streaming chat responses, and comprehensive infrastructure orchestration using .NET Aspire.