GraphRag.Net and typical-rag-dotnet
About GraphRag.Net
shuyu-labs/GraphRag.Net
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
This project helps you turn large collections of documents, like research papers or company reports, into an organized knowledge graph that you can easily query. It takes your raw text documents, extracts key entities and their relationships, and then structures them into an interactive graph. Researchers, analysts, or anyone dealing with extensive text-based information can use this to gain deeper insights and ask complex questions that go beyond simple keyword searches.
About typical-rag-dotnet
NikiforovAll/typical-rag-dotnet
Typical RAG implementation using Semantic Kernel, Semantic Memory and Aspire
This project helps developers build Retrieval-Augmented Generation (RAG) applications. It takes your documents, like PDFs, ingests them, and then allows users to ask questions in natural language. The output is a precise answer drawn from your documents, along with the source material, making it easier to build intelligent assistants.
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