There are 7 repositories under semantic-kernel topic.
12 Lessons to Get Started Building AI Agents
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
Five lessons, learn how to really apply AI to your .NET Applications
C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.
Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.
AI-in-a-Box leverages the expertise of Microsoft across the globe to develop and provide AI and ML solutions to the technical community. Our intent is to present a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction.
A new-age AI desktop tool
MCPSharp is a .NET library that helps you build Model Context Protocol (MCP) servers and clients - the standardized API protocol used by AI assistants and models.
Immersive workshop showcasing the remarkable potential of integrating SoTA foundation models to enhance product experiences and streamline backend workflows. Leverages Microsoft's Copilot stack, Microsoft Agent Framework and Azure primitives to offer an engaging and comprehensive introduction to AI-infused app development and deployment
skUnit is a testing tool for AI units, such as IChatClient, MCP Servers and SK kernels.
Tutorial for ChatGPT + Enterprise Data with Semantic Kernel, OpenAI, and Azure Cognitive Search
A collection of C# notebooks to get you started with Semantic Kernel quickly.
Facilitates creating modular specialized agents that coordinate across diverse data types and tools like M365 and Teams to assist multi-disciplinary healthcare workflows—such as cancer care.
A Blazor Web App and Minimal API for performing RAG (Retrieval Augmented Generation) and vector search using the native VECTOR type in Azure SQL Database and Azure OpenAI.
Microsoft Semantic Kernel Assistants This enables the usage of assistants for the Semantic Kernel. It provides different scenarios for the usage of assistants such as: Assistant with Semantic Kernel plugins Multi-Assistant conversation
🌟DataTonic : A Data-Capable AGI-style Agent Builder of Agents , that creates swarms , runs commands and securely processes and creates datasets, databases, visualisations, and analyses.
Some experiments around AI to learn.
A creative writing multi-agent solution to help users write articles using Aspire and Semantic Kernel
A multi-agent chatroom for AutoGen agents
A sample Chatbot in C# using Microsoft Agent Framework
A ChatGPT plugin built with Semantic Kernel that queries a database via natural language. Winner of Microsoft's first Semantic Kernel hackathon in the "Most Useful for the Enterprise" category.
A planner that integrates into Semantic Kernel to enable function calling on all Chat based LLMs (Mistral, Bard, Claude, LLama etc)
👩🏻🔬🧪SciTonic is a highly adaptive technical operator of agents that can produce complexe analyses on technical data with high performance & on-the-fly . You can ask it what you want and it will respond with quality everytime.
Some Cool Semantic Kernel Plugins
Semantic Kernel Connector to DashScope
A collection of Plugins and example console application built on the Semantic Kernel
This is an AI agent playground to demonstrate different agent orchestration patterns and capabilities
AI-driven peds for GTA V/FiveM using GPT, enhancing gameplay with realistic, engaging autonomous agents on .NET.
Sample for context-aware Agentic RaG, Q&A with multi-source verification, and self-curating knowledge base. Powered by Azure AI Foundry Agent Service, Azure AI Search with agentic retrieval and query rewrite, Semantic Kernel and LangGraph agents running in Azure Container Apps, and ready for Copilot Studio
A lightweight implementation of Kernel Memory as a Service
Powerful tool designed to generate SQL queries from natural language (NL2SQL) using Microsoft’s Semantic Kernel framework. This project aims to bridge the gap between human-readable queries and SQL, enabling easy and efficient database interactions with AI-driven language models.
Semantic Kernel 集成文心千帆
A sample for implementing retrieval augmented generation using Azure Open AI to generate embeddings, Azure Cosmos DB for MongoDB vCore to perform vector search, and semantic kernel.
Learning Azure AI with APIM, Semantic Kernel and LangChain.