updated readme

Author: yorek

README.md

@@ -17,18 +17,17 @@ products:
 - azure-sqlserver-vm
 - dotnet
 - azure-openai
-urlFragment: azure-sql-db-session-recommender
-name: Session Recommender using Azure SQL DB, Open AI and Vector Search
+name: Retriveal Augmented Generation with Azure SQL DB and OpenAI
 description: Build a session recommender using Jamstack and Event-Driven architecture, using Azure SQL DB to store and search vectors embeddings generated using OpenAI
 ---
-<!-- YAML front-matter schema: https://review.learn.microsoft.com/en-us/help/contribute/samples/process/onboarding?branch=main#supported-metadata-fields-for-readmemd -->
-
 # Session Assistant Sample - Retriveal Augmented Generation with Azure SQL DB and OpenAI
 
 This sample demonstrates how to build a session recommender using Jamstack and Event-Driven architecture, using Azure SQL DB to store and search vectors embeddings generated using OpenAI. The solution is built using Azure Static Web Apps, Azure Functions, Azure SQL Database, and Azure OpenAI.
 
 A fully working, production ready, version of this sample, that has been used at [VS Live](https://vslive.com/) conferences, is available here: https://ai.lasvegas.vslive.com/
 
+![Retrieval Augmented Generator flow](./_docs/rag.png)
+
 This repository is a evoution of the [Session Recommender](https://github.com/azure-samples/azure-sql-db-session-recommender) sample. In addition to vector search, also Retrival Augmented Generation (RAG) is used to generate the response to the user query. If you are completely new to this topic, you may want to start there, and then come back here.
 
 ![Architecture Diagram](./_docs/session-recommender-architecture.png)