From 1c7755618579cc291332d9c6d63b2435a7029d29 Mon Sep 17 00:00:00 2001 From: sykp241095 Date: Tue, 4 Jun 2024 15:06:37 +0800 Subject: [PATCH] Update README.md --- examples/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/README.md b/examples/README.md index a2dd3e9..70876f6 100644 --- a/examples/README.md +++ b/examples/README.md @@ -30,7 +30,7 @@ Please make sure you have created a TiDB Serverless cluster with vector support - [LlamaIndex RAG with UI](./llamaindex-tidb-vector-with-ui/README.md): use the LlamaIndex to build an [RAG(Retrieval-Augmented Generation)](https://docs.llamaindex.ai/en/latest/getting_started/concepts/) application. - [Chat with URL](./llamaindex-tidb-vector/README.md): use LlamaIndex to build an [RAG(Retrieval-Augmented Generation)](https://docs.llamaindex.ai/en/latest/getting_started/concepts/) application that can chat with a URL. - [GraphRAG](./graphrag-demo/README.md): 20 lines code of using TiDB Serverless to build a Knowledge Graph based RAG application. -- [GraphRAG Step by Step Tutorial](./graphrag-step-by-step-tutorial/README.md): Step by step tutorial to build a Knowledge Graph based RAG application with Colab notebook. In this tutorial, you will learn how to extract knowledge from a text corpus, build a Knowledge Graph, store the Knowledge Graph in TiDB Serverless, and search from the Knowledge Graph. +- [GraphRAG Step by Step Tutorial](./graphrag-step-by-step-tutorial/README.md): Step by step tutorial to build a Knowledge Graph based RAG application with [DSPy](https://github.com/stanfordnlp/dspy) and TiDB Serverless Vector Storage. In this tutorial, you will learn how to extract knowledge from a text corpus, build a Knowledge Graph, store the Knowledge Graph in TiDB Serverless, and search from the Knowledge Graph. ## Real World Applications