updated readme

Author: yorek

README.md

@@ -1,24 +1,119 @@
-Coming Soon!
+---
+page_type: sample
+languages:
+- azdeveloper
+- csharp
+- sql
+- tsql
+- javascript
+- html
+- bicep
+products:
+- azure-functions
+- azure-sql-database
+- static-web-apps
+- sql-server
+- azure-sql-managed-instance
+- azure-sqlserver-vm
+- dotnet
+- azure-openai
+urlFragment: azure-sql-db-session-recommender
+name: Session Recommender using Azure SQL DB, Open AI and Vector Search
+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 -->
 
-In the meantime take a look at v1 of this project:
+# Session Assistant Sample - Retrieveal Augmented Generation with Azure SQL DB and OpenAI
 
-- https://sessionfinder.dotnetconf.net/
-- https://github.com/Azure-Samples/azure-sql-db-session-recommender
+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.
 
-Coming Soon!
+![Architecture Diagram](./_docs/session-recommender-architecture.png)
 
-In the meantime take a look at v1 of this project:
+A session recommender built using
 
-- https://sessionfinder.dotnetconf.net/
-- https://github.com/Azure-Samples/azure-sql-db-session-recommender
+- [Azure Static Web Apps](https://learn.microsoft.com/en-us/azure/static-web-apps/overview)
+- [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/openai/)
+- [Azure Functions](https://learn.microsoft.com/en-us/azure/azure-functions/functions-overview?pivots=programming-language-csharp)
+- [Azure SQL Database](https://www.sqlservercentral.com/articles/the-sql-developer-experience-beyond-rdbms)
+- [Data API builder](https://aka.ms/dab)
 
-# Session Recommender V2
+For more details on the solution check also the following articles:
 
-Coming soon...
+- [How I built a session recommender in 1 hour using Open AI](https://dev.to/azure/how-i-built-a-session-recommender-in-1-hour-using-open-ai-5419)
+- [Vector Similarity Search with Azure SQL database and OpenAI](https://devblogs.microsoft.com/azure-sql/vector-similarity-search-with-azure-sql-database-and-openai/)
 
+# Deploy the sample using the Azure Developer CLI (azd) template
 
+The Azure Developer CLI (`azd`) is a developer-centric command-line interface (CLI) tool for creating Azure applications.
+
+## Prerequisites
+
+- Install [AZD CLI](https://learn.microsoft.com/azure/developer/azure-developer-cli/install-azd).
+- Install [.NET SDK](https://dotnet.microsoft.com/download).
+- Install [Node.js](https://nodejs.org/download/).
+- Install [SWA CLI](https://azure.github.io/static-web-apps-cli/docs/use/install#installing-the-cli).
+
+## Install AZD CLI
+
+You need to install it before running and deploying with the Azure Developer CLI.
+
+### Windows
+
+```powershell
+powershell -ex AllSigned -c "Invoke-RestMethod 'https://aka.ms/install-azd.ps1' | Invoke-Expression"
+```
+
+### Linux/MacOS
+
+```bash
+curl -fsSL https://aka.ms/install-azd.sh | bash
+```
+
+After logging in with the following command, you will be able to use azd cli to quickly provision and deploy the application.
+
+## Authenticate with Azure
+
+Make sure AZD CLI can access Azure resources. You can use the following command to log in to Azure:
+
+```bash
+azd auth login
 ```
 
+## Initialize the template
+
+Then, execute the `azd init` command to initialize the environment (You do not need to run this command if you already have the code or have opened this in a Codespace or DevContainer).
+
+```bash
+azd init -t Azure-Samples/azure-sql-db-session-recommender-v2
+```
+
+Enter an environment name.
+
+## Deploy the sample
+
+Run `azd up` to provision all the resources to Azure and deploy the code to those resources.
+
+```bash
+azd up 
+```
+
+Select your desired `subscription` and `location`. Then choose a resource group or create a new resource group. Wait a moment for the resource deployment to complete, click the Website endpoint and you will see the web app page.
+
+**Note**: Make sure to pick a region where all services are available like, for example, *West Europe* or *East US 2*
+
+## GitHub Actions
+
+Using the Azure Developer CLI, you can setup your pipelines, monitor your application, test and debug locally.
+
+```bash
+azd pipeline config
+```
+
+## Test the solution
+
+Add a new row to the `Sessions` table using the following SQL statement (you can use tools like [Azure Data Studio](https://learn.microsoft.com/en-us/azure-data-studio/quickstart-sql-database) or [SQL Server Management Studio](https://learn.microsoft.com/en-us/azure/azure-sql/database/connect-query-ssms?view=azuresql) to connect to the database. No need to install them if you don't want. In that case you can use the [SQL Editor in the Azure Portal](https://learn.microsoft.com/en-us/azure/azure-sql/database/connect-query-portal?view=azuresql)):
+
+```sql
 insert into web.sessions 
     (title, abstract, external_id, start_time_PST, end_time_PST, require_embeddings_update)
 values
@@ -30,10 +125,34 @@ values
         '2024-03-10 11:00:00',
         1
     )
+```
+
+immediately the deployed Azure Function will get executed in response to the `INSERT` statement. The Azure Function will call the OpenAI service to generate the text embedding for the session title and abstract, and then store the embedding in the database, specifically in the `web.sessions_embeddings` table.
 
+```sql
+select * from web.sessions_embeddings
 ```
 
+You can now open the URL associated with the created Static Web App to see the session recommender in action. You can get the URL from the Static Web App overview page in the Azure portal.
+
+![Website running](./_docs/session-recommender.png)
+
+## Run the solution locally
+
+The whole solution can be executed locally, using [Static Web App CLI](https://github.com/Azure/static-web-apps-cli) and [Azure Function CLI](https://learn.microsoft.com/en-us/azure/azure-functions/functions-run-local?tabs=windows%2Cisolated-process%2Cnode-v4%2Cpython-v2%2Chttp-trigger%2Ccontainer-apps&pivots=programming-language-csharp).
+
+Install the required node packages needed by the fronted:
+
+```bash
+cd client
+npm install
 ```
+
+once finished, create a `./func/local.settings.json` and `.env` starting from provided samples files, and fill out the settings using the correct values for your environment.
+
+From the sample root folder run:
+
+```bash
 swa start ./client --api-location ./func --data-api-location ./swa-db-connections
 ```
 
@@ -42,4 +161,8 @@ swa start ./client --api-location ./func --data-api-location ./swa-db-connection
 The solution uses Fluent UI for the UI components. The Fluent UI is a collection of UX frameworks from Microsoft that provides a consistent design language for web, mobile, and desktop applications. More details about Fluent UI can be found at the following links: 
 
 - https://github.com/microsoft/fluentui
-- https://react.fluentui.dev/ 
+- https://react.fluentui.dev/ 
+
+## Credits
+
+Thanks a lot to [Aaron Powell](https://www.aaron-powell.com/) for having helped in building the RAG sample, doing a complete UI revamp using the Fluent UI and for the implementaiton of the `ask` endpoint.