RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
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Updated
Nov 3, 2025 - C#
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
eShopLite is a set of reference .NET applications implementing an eCommerce site with features like Semantic Search, MCP, Reasoning models and more.
The .NET library to build AI agents with 25+ built-in connectors.
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.
参考GraphRag使用 Semantic Kernel 来实现的dotnet版本,可以使用NuGet开箱即用集成到项目中
eShopLite - Semantic Search is a reference .NET application implementing an eCommerce site with Search features using Keyword Search and Semantic Search.
A versatile multi-modal chat application that enables users to develop custom agents, create images, leverage visual recognition, and engage in voice interactions. It integrates seamlessly with local LLMs and commercial models like OpenAI, Gemini, Perplexity, and Claude, and allows to converse with uploaded documents and websites.
SQL Server connector for Semantic Kernel plugin and Kernel Memory
Microsoft's Kernel Memory StructRAG implementation
Semantic search in Unity!
eShopLite - Semantic Search is a reference .NET application implementing an eCommerce site with Search features using Keyword Search and Semantic Search with Azure AI Search
Typical RAG implementation using Semantic Kernel, Semantic Memory and Aspire
This example shows how a multitenant service can distribute requests evenly among multiple Azure OpenAI Service instances and manage tokens per minute (TPM) for multiple tenants.
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