RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
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Updated
Jan 20, 2025 - C#
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
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
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.
Lightweight In-memory Text Vector Database to embed in any .NET Applications
Semantic search in Unity!
SQL Server connector for Semantic Kernel plugin and Kernel Memory
A repository that showcases the native VECTOR type in Azure SQL Database to perform embeddings and RAG with Azure OpenAI.
Microsoft's Kernel Memory StructRAG implementation
A lightweight implementation of Kernel Memory as a Service
SQL Server as a vector database, SQL Server Extenstion for RAG
Implements a framework to build Generative AI applications.
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
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.
Explore AI Capabilities for Your .NET Projects with OpenAI's API: Unlock the power of AI in your applications
Typical RAG implementation using Semantic Kernel, Semantic Memory and Aspire
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