Task 01 - Deploy resources via a Bicep script (20 minutes)

In order to fork this repository, make sure that you are signed in to GitHub with the account you would like to use. Then, select the Fork button.

On the next page, select your account as the Owner and leave the repository name alone. Then, select Create fork to complete the process.

Ensure that you have the following software installed:

1. Visual Studio Code (Alternatively, if you have Visual Studio installed, you can use that.)
2. Install the following extensions in Visual Studio Code:
   • C# Dev Kit
   • Bicep
   • Azure Functions extension
   • Azure Storage extension
3. Install the Azure Functions Core Tools, which enables an integrated local debugging experience.
4. The Microsoft .NET 8.0 SDK. Ensure that you have the latest version of the SDK, not the Runtime.
5. The Azure Command Line Interface.
6. The Azure Developer CLI.
7. A Git client. An alternative option is to install GitHub Desktop.

8. Python 3.10 or later. You can run all of the exercises in this lab using a standard installation of Python and do not need the Anaconda Distribution of Python. If you do have Anaconda, make sure that you can execute Python and pip commands from the command line.

   Regardless of which distribution you use, make sure that you can run python and pip from your command line. If you are not sure whether you have pip installed, run python -m ensurepip to check.

If you are working from a local machine or non-Codespaces VM, you will also need to clone your forked repository to the local machine.

If you are creating a GitHub Codespace, select the Code button on your repository. Then, in the Codespaces tab, select the Create codespace on main button. This will instantiate a Codespace.

If you are cloning your repository, select the Code button and then choose the Local tab. Copy the URL in the box. Then, to clone the repository, open a terminal and navigate to to the directory in which you’d like to clone your repository. Use the command git clone {YOUR REPOSITORY URL} to clone to this location.

To create a virtual environment, perform the following steps:

1. Open up a terminal to the root directory of your Git repo. For example, if you cloned the repo to C:\SourceCode\TechExcel-Integrating-Azure-PaaS-and-AI-Services-for-AI-Design-Wins, open this directory in a command prompt. If you are using GitHub Codespaces, open a new terminal in Visual Studio Code–this will default you to the correct directory.
2. Run the following command: python -m venv aiwins. This will create a new virtual environment in the root directory named “aiwins” and make it available.
3. Run the following command to activate the virtual environment on MacOS or Linux (including GitHub Codespaces): source aiwins/bin/activate. If you are running this in Windows Subsystem for Linux, run the command source aiwins/Scripts/active. On Windows using CMD or PowerShell, use aiwins\Scripts\activate.bat to activate the virtual environment. Be sure to have the virtual environment active in every console or terminal you use throughout this training!

In a normal terminal or command prompt, you will see (aiwins) before your input prompt. This will let you know that you are working in a Python virtual environment. If you are using the Visual Studio Code terminal, this may not appear for technical reasons. You can mouse over the terminal image to ensure that the virtual environment is active for your terminal.

You will need to activate the virtual environment on every new terminal you use. When you are done, you can return to your standard Python environment by running deactivate in any environment. Alternatively, you may safely close the console or terminal without deactivation if you desire–it will not harm anything.

In order to install requirements, make sure that you are in a terminal connected to your virtual environment. Then, navigate to the src/ContosoSuitesDashboard folder and execute the command pip install -r requirements.txt. This will take several minutes to install but will include all of the Python package requirements necessary for the workshop.

1. Using the Terminal window in VS Code, execute the following commands to login:

az login
azd auth login

If you wish to use a subscription that does not belong to the home tenant of your user account, specify your TenantId by using the --tenant <yourtenantid> flag.

1. Using the Terminal window in VSCode, start the Azure Developer deployment process by running:

   azd up
   

2. Enter a new environment name (i.e. ‘techexcel1’).
3. Select the desired target Azure subscription for deployment. This subscription must have access to Azure OpenAI.
4. Select a deployment location. See notes below

You must deploy to an Azure region that supports the GPT-4o, 2024-05-13 model. You must create your Azure OpenAI resource in one of the supported regions.

Abstractive summarization in the Azure AI Services Language service is only supported in a subset of regions. You must create your Azure AI Language service in one of the supported regions to allow abstractive summarization to be performed in a later exercise.

1. Navigate to the Users blade in the Entra ID service for your Azure subscription. Find your user account and copy the User principal name and Object ID values. Use these values when prompted for the SqlAdminUserName and SqlAdminSid respectively.

   You may receive an error while running this that you must accept the Responsible AI Notice before creating a TextAnalytics (Language) service. To do so, open the Azure Portal and search for “Language” in the menu. Choose the Language service and then select Create. On the first page of the form, select the Continue to create your resource button at the bottom of the screen. Then, check the box certifying that you have reviewed and acknowledge the terms in the Responsible AI Notice. You can then close the Create Language page and try running the Bicep script again.

2. Once your deployment completes (about 5-10 minutes), you should see all of your resources in a new resource group based on your environment name (i.e. rg-techexcel1). These include: an API Management service, an App Service (for API), an App Service (for dashboard), an App Service plan (for API and dashboard), an App Service plan (for Function app), an Application Insights instance, an Azure Cosmos DB account, an Azure OpenAI workspace, a Container registry, a Function App, a Language service, a Log Analytics workspace, a Search service, a Speech service, a SQL database, a SQL server, and a Storage account.