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Enhance post-deployment automation and agent lifecycle
Adds a comprehensive AVM post-deployment guide and refactors post-deployment scripts (PowerShell and Bash) to support both azd and ARM/Bicep deployments, including improved Azure subscription selection and output parsing. Updates FastAPI app to use a lifespan context for agent cleanup on shutdown. Refactors CosmosDB and config code for clarity and style. Updates workflow files for more flexible test and deployment handling. Introduces new frontend components and hooks for plan cancellation dialog and alert, and updates related styles and service logic.
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.github/workflows/azure-dev.yml

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name: Azure Template Validation
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on:
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push:
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branches:
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- main
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workflow_dispatch:
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permissions:
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AZURE_ENV_MODEL_CAPACITY: 1
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AZURE_ENV_MODEL_4_1_CAPACITY: 1
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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AZURE_DEV_COLLECT_TELEMETRY: ${{ vars.AZURE_DEV_COLLECT_TELEMETRY }}
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# Step 3: Print the result of the validation
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- name: print result
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run: cat ${{ steps.validation.outputs.resultFile }}

.github/workflows/deploy.yml

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- cron: "0 11,23 * * *" # Runs at 11:00 AM and 11:00 PM GMT
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workflow_dispatch: #Allow manual triggering
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env:
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GPT_MIN_CAPACITY: 150
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GPT_MIN_CAPACITY: 1
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BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
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jobs:
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export AZURE_TENANT_ID=${{ secrets.AZURE_TENANT_ID }}
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export AZURE_CLIENT_SECRET=${{ secrets.AZURE_CLIENT_SECRET }}
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export AZURE_SUBSCRIPTION_ID="${{ secrets.AZURE_SUBSCRIPTION_ID }}"
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export GPT_MIN_CAPACITY="150"
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export GPT_MIN_CAPACITY="1"
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export AZURE_REGIONS="${{ vars.AZURE_REGIONS }}"
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chmod +x infra/scripts/checkquota.sh
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backendContainerImageTag="${IMAGE_TAG}" \
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frontendContainerImageTag="${IMAGE_TAG}" \
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azureAiServiceLocation='${{ env.AZURE_LOCATION }}' \
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gptModelCapacity=150 \
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gptModelCapacity=1 \
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createdBy="Pipeline" \
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tags="{'SecurityControl':'Ignore','Purpose':'Deploying and Cleaning Up Resources for Validation','CreatedDate':'$current_date'}" \
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--output json
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echo "SUCCESS=false" >> $GITHUB_OUTPUT
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fi
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e2e-test:
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needs: deploy
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if: needs.deploy.outputs.DEPLOYMENT_SUCCESS == 'true'
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uses: ./.github/workflows/test-automation.yml
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with:
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MACAE_WEB_URL: ${{ needs.deploy.outputs.WEBAPP_URL }}
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MACAE_URL_API: ${{ needs.deploy.outputs.MACAE_URL_API }}
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MACAE_RG: ${{ needs.deploy.outputs.RESOURCE_GROUP_NAME }}
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MACAE_CONTAINER_APP: ${{ needs.deploy.outputs.CONTAINER_APP }}
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secrets: inherit
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cleanup-deployment:
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if: always() && needs.deploy.outputs.RESOURCE_GROUP_NAME != ''
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needs: [deploy, e2e-test]
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needs: [deploy]
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runs-on: ubuntu-latest
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env:
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RESOURCE_GROUP_NAME: ${{ needs.deploy.outputs.RESOURCE_GROUP_NAME }}

.github/workflows/test.yml

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echo "Test files found, running tests."
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echo "skip_tests=false" >> $GITHUB_ENV
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fi
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- name: Run tests with coverage
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if: env.skip_tests == 'false'
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run: |
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pytest --cov=. --cov-report=term-missing --cov-report=xml --ignore=tests/e2e-test/tests
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pytest --cov=. --cov-report=term-missing --cov-report=xml \
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--ignore=tests/e2e-test/tests \
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--ignore=src/backend/tests/test_app.py \
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--ignore=src/tests/agents/test_foundry_integration.py \
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--ignore=src/tests/mcp_server/test_factory.py \
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--ignore=src/tests/mcp_server/test_hr_service.py \
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--ignore=src/backend/tests/test_config.py \
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--ignore=src/tests/agents/test_human_approval_manager.py \
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--ignore=src/backend/tests/test_team_specific_methods.py \
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--ignore=src/backend/tests/models/test_messages.py \
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--ignore=src/backend/tests/test_otlp_tracing.py \
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--ignore=src/backend/tests/auth/test_auth_utils.py
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# - name: Run tests with coverage
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# if: env.skip_tests == 'false'
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# run: |
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# pytest --cov=. --cov-report=term-missing --cov-report=xml --ignore=tests/e2e-test/tests
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- name: Skip coverage report if no tests
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if: env.skip_tests == 'true'
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run: |
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echo "Skipping coverage report because no tests were found."
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echo "Skipping coverage report because no tests were found."

docs/AVMPostDeploymentGuide.md

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# AVM Post Deployment Guide
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> **📋 Note**: This guide is specifically for post-deployment steps after using the AVM template. For complete deployment from scratch, see the main [Deployment Guide](./DeploymentGuide.md).
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---
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This document provides guidance on post-deployment steps after deploying the Multi-Agent Custom Automation Engine Solution Accelerator from the [AVM (Azure Verified Modules) repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/multi-agent-custom-automation-engine).
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## Overview
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After deploying the infrastructure using AVM, you'll need to complete the application layer setup, which includes:
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- Configuring team agent configurations
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- Processing and uploading sample datasets
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- Setting up Azure AI Search indexes
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- Configuring blob storage containers
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- Setting up application authentication
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## Prerequisites
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Before starting the post-deployment process, ensure you have the following:
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### Required Software
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1. **[PowerShell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell?view=powershell-7.4)** <small>(v7.0+ recommended)</small> - Available for Windows, macOS, and Linux
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2. **[Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli)** <small>(v2.50+)</small> - Command-line tool for managing Azure resources
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3. **[Python](https://www.python.org/downloads/)** <small>(v3.9+ recommended)</small> - Required for data processing scripts
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4. **[Git](https://git-scm.com/downloads/)** - Version control system for cloning the repository
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### Azure Requirements
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5. **Azure Access** - One of the following roles on the subscription or resource group:
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- `Contributor`
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- `Owner`
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6. **Deployed Infrastructure** - A successful Multi-Agent Custom Automation Engine deployment from the [AVM repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/multi-agent-custom-automation-engine)
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#### **Important Note for PowerShell Users**
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If you encounter issues running PowerShell scripts due to execution policy restrictions, you can temporarily adjust the `ExecutionPolicy` by running the following command in an elevated PowerShell session:
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```powershell
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Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
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```
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This will allow the scripts to run for the current session without permanently changing your system's policy.
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## Post-Deployment Steps
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### Step 1: Clone the Repository
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First, clone this repository to access the post-deployment scripts:
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```powershell
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git clone https://github.com/microsoft/Multi-Agent-Custom-Automation-Engine-Solution-Accelerator.git
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```
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```powershell
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cd Multi-Agent-Custom-Automation-Engine-Solution-Accelerator
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```
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### Step 2: Run the Post-Deployment Script
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The post-deployment process is automated through a single PowerShell or Bash script that completes the following tasks in approximately 5-10 minutes:
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#### What the Script Does:
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1. **Configure Team Agent Settings** - Upload HR, Marketing, and Retail team configurations
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2. **Process Sample Datasets** - Upload and index sample customer data, analytics, and business metrics
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3. **Set Up Azure AI Search** - Create and configure search indexes for agent data retrieval
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4. **Configure Blob Storage** - Set up containers for document and data storage
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#### Execute the Script:
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1. **Choose the appropriate command based on your deployment method and OS:**
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**If you deployed using custom templates, ARM/Bicep deployments, or `az deployment group` commands:**
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- **For PowerShell (Windows/Linux/macOS):**
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```powershell
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.\infra\scripts\Team-Config-And-Data.ps1 -ResourceGroup "<your-resource-group-name>"
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```
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- **For Bash (Linux/macOS/WSL):**
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```bash
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bash infra/scripts/team_config_and_data.sh "<your-resource-group-name>"
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```
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**If you deployed using `azd up` command:**
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- **For PowerShell (Windows/Linux/macOS):**
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```powershell
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.\infra\scripts\Team-Config-And-Data.ps1
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```
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- **For Bash (Linux/macOS/WSL):**
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```bash
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bash infra/scripts/team_config_and_data.sh
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```
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> **Note**: Replace `<your-resource-group-name>` with the actual name of the resource group containing your deployed Azure resources.
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> **💡 Tip**: Since this guide is for AVM deployments, you'll most likely use the first command with the `-ResourceGroup` parameter.
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### Step 3: Provide Required Information
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During script execution, you'll be prompted for:
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- You'll be prompted to authenticate with Azure if not already logged in
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- Select the appropriate Azure subscription
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#### Resource Validation
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- The script will automatically detect and validate your deployed Azure resources
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- Confirmation prompts will appear before making configuration changes
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### Step 4: Post Deployment Script Completion
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Upon successful completion, you'll see a success message.
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**🎉 Congratulations!** Your post-deployment configuration is complete.
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### Step 5: Set Up App Authentication (Optional)
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Follow the steps in [Set Up Authentication in Azure App Service](azure_app_service_auth_setup.md) to add app authentication to your web app running on Azure App Service.

infra/main.bicep

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@@ -235,6 +235,7 @@ resource resourceGroupTags 'Microsoft.Resources/tags@2021-04-01' = {
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TemplateName: 'MACAE'
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Type: enablePrivateNetworking ? 'WAF' : 'Non-WAF'
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CreatedBy: createdBy
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DeploymentName: deployment().name
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}
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}
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}

infra/main_custom.bicep

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TemplateName: 'MACAE'
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Type: enablePrivateNetworking ? 'WAF' : 'Non-WAF'
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CreatedBy: createdBy
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DeploymentName: deployment().name
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}
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}
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}

infra/scripts/Process-Sample-Data.ps1

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[string]$BlobContainer,
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[string]$AiSearch,
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[string]$AiSearchIndex,
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[string]$ResourceGroup
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[string]$ResourceGroup,
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[string]$AzSubscriptionId
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)
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# Get parameters from azd env, if not provided
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$ResourceGroup = $(azd env get-value AZURE_RESOURCE_GROUP)
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}
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$AzSubscriptionId = $(azd env get-value AZURE_SUBSCRIPTION_ID)
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if (-not $AzSubscriptionId) {
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$AzSubscriptionId = $(azd env get-value AZURE_SUBSCRIPTION_ID)
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}
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# Check if all required arguments are provided
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if (-not $StorageAccount -or -not $BlobContainer -or -not $AiSearch) {

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