LLM-RAG-Architecture and dotnet-rag-api

These are ecosystem siblings—one provides a generalizable RAG architecture reference implementation while the other is a specialized .NET 8 API implementation that could adopt or be compared against that architecture pattern.

LLM-RAG-Architecture
42
Emerging
dotnet-rag-api
36
Emerging
Maintenance 6/25
Adoption 7/25
Maturity 13/25
Community 16/25
Maintenance 10/25
Adoption 3/25
Maturity 11/25
Community 12/25
Stars: 27
Forks: 7
Downloads:
Commits (30d): 0
Language: C#
License: MIT
Stars: 4
Forks: 1
Downloads:
Commits (30d): 0
Language: C#
License: MIT
No Package No Dependents
No Package No Dependents

About LLM-RAG-Architecture

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.

knowledge-management document-intelligence enterprise-search technical-documentation information-retrieval

About dotnet-rag-api

Argha713/dotnet-rag-api

A production-ready RAG (Retrieval-Augmented Generation) API built with .NET 8. Upload documents, ask questions, and get AI-powered answers with source citations and streaming support.

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