matt-bentley/LLM-RAG-Architecture
Production-grade Retrieval Augmented Generation (RAG) architecture using Open Source components
This system helps professionals get accurate answers and insights from large collections of internal documents, like company policies, research papers, or technical manuals. You feed it PDF documents, and it allows you to ask questions in plain language, receiving summarized answers with citations to the original sources. This is designed for knowledge workers, researchers, or operations teams who need to quickly find information within their own organizational knowledge base.
Use this if you need a reliable way to search and query your internal documents, getting precise answers without sifting through pages of text manually.
Not ideal if you're looking for a simple keyword search tool or if your documents are highly unstructured and don't require deep contextual understanding.
Stars
27
Forks
7
Language
C#
License
MIT
Category
Last pushed
Jan 12, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/matt-bentley/LLM-RAG-Architecture"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
nashtech-garage/ntg-agent
A sample Chatbot in C# using Microsoft Agent Framework
shuyu-labs/AntSK
An AI knowledge base/agent built with .Net 9, AntBlazor, Semantic Kernel, and Kernel Memory,...
Azure-Samples/azure-ai-search-multimodal-sample
A sample app for the Multimodal Retrieval-Augmented Generation pattern running in Azure, using...
Azure-Samples/contoso-real-estate
Intelligent enterprise-grade reference architecture for JavaScript, featuring OpenAI...
wisedev-code/MaIN.NET
NuGet package designed to make LLMs, RAG, and Agents first-class citizens in .NET