examples: add runnable vector search demos on sqlalchemy (#34)

sykp241095 · web-flow · commit 87e34f0f4355 · 2024-06-11T16:56:11.000+08:00
diff --git a/examples/README.md b/examples/README.md
@@ -31,6 +31,7 @@ Please make sure you have created a TiDB Serverless cluster with vector support
 - [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.
+- [Vector Search Notebook with SQLAlchemy](https://colab.research.google.com/drive/1LuJn4mtKsjr3lHbzMa2RM-oroUvpy83y?usp=sharing): use [SQLAlchemy](https://www.sqlalchemy.org/) to interact with TiDB Serverless: connect db, index&store data and then search vectors.
 
 ## Real World Applications
 
