chore: Dev to Main merge

.env.sample

@@ -17,7 +17,7 @@ USE_FOUNDRY=false
 AZURE_AI_PROJECT_ENDPOINT=
 
 # Image model deployment name in Foundry (e.g., gpt-image-1-mini)
-AZURE_AI_IMAGE_DEPLOYMENT=gpt-image-1-mini
+AZURE_AI_IMAGE_MODEL_DEPLOYMENT=gpt-image-1-mini
 
 # =============================================================================
 # Azure OpenAI Configuration

docs/AVMPostDeploymentGuide.md

@@ -0,0 +1,211 @@
+# AVM Post Deployment Guide
+
+> **📋 Note**: This guide is specifically for post-deployment steps after using the AVM template. For complete deployment from scratch, see the main [Deployment Guide](./DEPLOYMENT.md).
+
+---
+
+This document provides guidance on post-deployment steps after deploying the Content Generation solution accelerator from the [AVM (Azure Verified Modules) repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/content-generation).
+
+## Overview
+
+After successfully deploying the Content Generation Solution Accelerator using the AVM template, you'll need to complete some configuration steps to make the solution fully operational. The AVM deployment provisions all required Azure resources, and the post-deployment process will upload sample data, create search indexes, and verify the application is ready to use.
+
+---
+
+## Prerequisites
+
+Before starting the post-deployment process, ensure you have the following:
+
+### 1. Azure Subscription & Permissions
+
+You need access to an [Azure subscription](https://azure.microsoft.com/free/) with permissions to:
+- Create resource groups and resources
+- Create app registrations
+- Assign roles at the resource group level (Contributor + RBAC)
+
+📖 Follow the steps in [Azure Account Set Up](./AzureAccountSetUp.md) for detailed instructions.
+
+### 2. Deployed Infrastructure
+
+A successful Content Generation solution accelerator deployment from the [AVM repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/content-generation).
+
+The deployment should have created the following resources:
+- Azure App Service (frontend web app)
+- Azure Container Instance (backend API)
+- Azure AI Foundry (AI orchestration)
+- Azure OpenAI Service (GPT and Image models)
+- Azure Cosmos DB (product catalog and conversations)
+- Azure Blob Storage (product images and generated images)
+- Azure AI Search (product search index)
+- User Assigned Managed Identity
+- App Service Plan
+
+**Optional resources** (depending on deployment parameters):
+- Log Analytics Workspace and Application Insights (if monitoring is enabled)
+- Virtual Network, Private DNS Zones, and Private Endpoints (if private networking is enabled)
+- Azure Bastion and Jumpbox VM (if enabled for private network administration)
+
+**Important:** The deployment references an **existing Azure Container Registry** (specified via the `acrName` parameter) that must contain pre-built container images (`content-gen-app` and `content-gen-api`). The ACR is not created by this deployment.
+
+### 3. Required Tools
+
+Ensure the following tools are installed on your machine:
+
+| Tool | Version | Download Link |
+|------|---------|---------------|
+| PowerShell | v7.0+ | [Install PowerShell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell?view=powershell-7.5) |
+| Azure CLI | v2.50+ | [Install Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli) |
+| Python | 3.11+ | [Download Python](https://www.python.org/downloads/) |
+| Git | Latest | [Download Git](https://git-scm.com/downloads) |
+
+#### Important Note for PowerShell Users
+
+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:
+
+```powershell
+Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
+```
+
+This will allow the scripts to run for the current session without permanently changing your system's policy.
+
+---
+
+## Post-Deployment Steps
+
+### Step 1: Clone the Repository
+
+Clone this repository to access the post-deployment scripts and sample data:
+
+```powershell
+git clone https://github.com/microsoft/content-generation-solution-accelerator.git
+cd content-generation-solution-accelerator
+```
+
+---
+
+### Step 2: Run the Post-Deployment Script
+
+The AVM deployment provisions the Azure infrastructure but does NOT include automated post-deployment hooks. You need to manually run the post-deployment script to upload sample data and create search indexes.
+
+> **📝 Note**: Unlike `azd up` deployments which run post-deployment hooks automatically via `azure.yaml`, AVM deployments require manual execution of the post-deployment script.
+
+#### 2.1 Login to Azure
+
+```shell
+az login
+```
+
+> 💡 **Tip**: If using VS Code Web or environments without browser access, use device code authentication:
+> ```shell
+> az login --use-device-code
+> ```
+
+#### 2.2 Set Up Environment
+
+Navigate to the repository root directory and create a Python virtual environment:
+
+**For Windows (PowerShell):**
+```powershell
+python -m venv .venv
+.\.venv\Scripts\Activate.ps1
+pip install -r ./scripts/requirements-post-deploy.txt
+```
+
+**For Linux/Mac (bash):**
+```bash
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r ./scripts/requirements-post-deploy.txt
+```
+
+#### 2.3 Execute the Post-Deployment Script
+
+Run the post-deployment script with your resource group name. The script will automatically retrieve resource names from the Azure deployment outputs.
+
+**For Windows (PowerShell):**
+```powershell
+python ./scripts/post_deploy.py -g <your-resource-group-name> --skip-tests
+```
+
+**For Linux/Mac (bash):**
+```bash
+python3 ./scripts/post_deploy.py -g <your-resource-group-name> --skip-tests
+```
+
+**Example:**
+```powershell
+python ./scripts/post_deploy.py -g rg-contentgen-prod --skip-tests
+```
+
+> ⚠️ **Important**: The script uses Azure CLI authentication and will automatically discover resource names from deployment outputs. Ensure you're logged in with `az login` before running.
+
+**How it works:**
+- The script queries the deployment outputs using the resource group name
+- It automatically retrieves App Service, Storage Account, Cosmos DB, and AI Search names
+- No need to manually specify individual resource names
+
+**Alternative:** If you prefer to specify resources explicitly, you can use environment variables or command-line arguments:
+```powershell
+# Using environment variables
+$env:RESOURCE_GROUP_NAME = "rg-contentgen-prod"
+$env:APP_SERVICE_NAME = "app-contentgen-abc123"
+$env:AZURE_BLOB_ACCOUNT_NAME = "stcontentgenabc123"
+$env:COSMOSDB_ACCOUNT_NAME = "cosmos-contentgen-abc123"
+$env:AI_SEARCH_SERVICE_NAME = "search-contentgen-abc123"
+python ./scripts/post_deploy.py --skip-tests
+```
+
+The script will:
+- Upload sample product data to Cosmos DB
+- Upload sample product images to Blob Storage
+- Create and populate the Azure AI Search index
+- Verify all connections and configurations
+
+---
+
+### Step 3: Access the Application
+
+1. Navigate to the [Azure Portal](https://portal.azure.com)
+2. Open the **resource group** created during deployment
+3. Locate the **App Service** (name typically starts with `app-contentgen-`)
+4. Copy the **URL** from the Overview page (format: `https://app-contentgen-<unique-id>.azurewebsites.net`)
+5. Open the URL in your browser to access the application
+
+> 📝 **Note**: It may take a few minutes for the App Service to start up after deployment.
+
+---
+
+### Step 4: Configure Authentication (Optional)
+
+If you want to enable authentication for your application, follow the [App Authentication Guide](./AppAuthentication.md).
+
+> **⚠️ Important**: Authentication changes can take up to 10 minutes to propagate.
+
+---
+
+### Step 5: Verify Data Processing
+
+Confirm your deployment is working correctly:
+
+| Check | Location | How to Verify |
+|-------|----------|---------------|
+| ✅ Sample data uploaded | Azure Cosmos DB | Navigate to Cosmos DB → Data Explorer → Check `products` and `conversations` containers |
+| ✅ Sample images uploaded | Azure Blob Storage | Navigate to Storage Account → Containers → Check `product-images` container |
+| ✅ AI Search index created | Azure AI Search | Navigate to AI Search → Indexes → Verify `products-index` exists and has documents |
+| ✅ Application loads | App Service URL | Open the web app URL and verify the welcome screen appears |
+
+---
+
+## Getting Started
+
+To learn how to use the Content Generation solution and try sample workflows, see the [Sample Workflow](./DEPLOYMENT.md#sample-workflow) section in the main Deployment Guide.
+
+---
+
+## Clean Up Resources
+
+If you need to delete the resources after testing or a failed deployment:
+
+Follow the steps in [Delete Resource Group](./DeleteResourceGroup.md) to clean up all deployed resources.
+
+> ⚠️ **Warning**: Deleting the resource group will permanently delete all resources and data. This action cannot be undone.

docs/CustomizingAzdParameters.md

@@ -10,14 +10,14 @@ By default this template will use the environment name as the prefix to prevent
 | -------------------------------------- | ------- | ---------------------------- | ----------------------------------------------------------------------------- |
 | `AZURE_LOCATION`                       | string  | `<User selects during deployment>` | Sets the Azure region for resource deployment. Allowed: `australiaeast`, `centralus`, `eastasia`, `eastus`, `eastus2`, `japaneast`, `northeurope`, `southeastasia`, `swedencentral`, `uksouth`, `westus`, `westus3`. |
 | `AZURE_ENV_NAME`                       | string  | `contentgen`               | Sets the environment name prefix for all Azure resources (3-15 characters).   |
-| `secondaryLocation`                    | string  | `uksouth`                  | Specifies a secondary Azure region for database creation.                     |
-| `gptModelName`                         | string  | `gpt-5.1`                 | Specifies the GPT model name to deploy.                                       |
-| `gptModelVersion`                      | string  | `2025-11-13`               | Sets the GPT model version.                                                   |
-| `gptModelDeploymentType`               | string  | `GlobalStandard`           | Defines the model deployment type (allowed: `Standard`, `GlobalStandard`).    |
-| `gptModelCapacity`                     | integer | `150`                      | Sets the GPT model token capacity (minimum: `10`).                            |
-| `imageModelChoice`                     | string  | `gpt-image-1-mini`             | Image model to deploy (allowed: `gpt-image-1-mini`, `gpt-image-1.5`, `none`). |
-| `imageModelCapacity`                   | integer | `1`                        | Sets the image model deployment capacity in RPM (minimum: `1`).               |
-| `azureOpenaiAPIVersion`                | string  | `2025-01-01-preview`       | Specifies the API version for Azure OpenAI service.                           |
+| `SECONDARY_LOCATION`                   | string  | `uksouth`                  | Specifies a secondary Azure region for database creation.                     |
+| `AZURE_OPENAI_GPT_MODEL`              | string  | `gpt-5.1`                 | Specifies the GPT model name to deploy.                                       |
+| `GPT_MODEL_VERSION`                    | string  | `2025-11-13`               | Sets the GPT model version.                                                   |
+| `GPT_MODEL_DEPLOYMENT_TYPE`            | string  | `GlobalStandard`           | Defines the model deployment type (allowed: `Standard`, `GlobalStandard`).    |
+| `GPT_MODEL_CAPACITY`                   | integer | `150`                      | Sets the GPT model token capacity (minimum: `10`).                            |
+| `AZURE_OPENAI_IMAGE_MODEL`             | string  | `gpt-image-1-mini`         | Image model to deploy (allowed: `gpt-image-1-mini`, `gpt-image-1.5`, `none`). |
+| `IMAGE_MODEL_CAPACITY`                 | integer | `1`                        | Sets the image model deployment capacity in RPM (minimum: `1`).               |
+| `AZURE_OPENAI_API_VERSION`             | string  | `2025-01-01-preview`       | Specifies the API version for Azure OpenAI service.                           |
 | `AZURE_ENV_OPENAI_LOCATION`           | string  | `<User selects during deployment>` | Sets the Azure region for OpenAI resource deployment.                         |
 | `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID` | string  | `""`                       | Reuses an existing Log Analytics Workspace instead of creating a new one.     |
 | `AZURE_EXISTING_AI_PROJECT_RESOURCE_ID`| string  | `""`                       | Reuses an existing AI Foundry Project instead of creating a new one.          |
@@ -36,8 +36,8 @@ azd env set <PARAMETER_NAME> <VALUE>
 
 ```bash
 azd env set AZURE_LOCATION westus2
-azd env set gptModelName gpt-5.1
-azd env set gptModelDeploymentType Standard
-azd env set imageModelChoice gpt-image-1-mini
+azd env set AZURE_OPENAI_GPT_MODEL gpt-5.1
+azd env set GPT_MODEL_DEPLOYMENT_TYPE Standard
+azd env set AZURE_OPENAI_IMAGE_MODEL gpt-image-1-mini
 azd env set ACR_NAME contentgencontainerreg
 ```

docs/DEPLOYMENT.md

@@ -137,7 +137,7 @@ When you start the deployment, most parameters will have **default values**, but
 | **GPT Model Version**                       | The version of the selected GPT model.                                                                    | 2025-11-13            |
 | **OpenAI API Version**                      | The Azure OpenAI API version to use.                                                                      | 2025-01-01-preview     |
 | **GPT Model Deployment Capacity**           | Configure capacity for **GPT models** (in thousands).                                                     | 150k                    |
-| **Image Model**                            | Choose from **gpt-image-1-mini, gpt-image-1.5**                                                                          | gpt-image-1-mini             |
+| **Image Model**                            | Choose from **gpt-image-1-mini, gpt-image-1.5**                                                                               | gpt-image-1-mini                  |
 | **Image Tag**                               | Docker image tag to deploy. Common values: `latest`, `dev`, `hotfix`.                                     | latest                 |
 | **Existing Log Analytics Workspace**        | To reuse an existing Log Analytics Workspace ID.                                                          | *(empty)*              |
 | **Existing Azure AI Foundry Project**       | To reuse an existing Azure AI Foundry Project ID instead of creating a new one.                           | *(empty)*              |

docs/TECHNICAL_GUIDE.md

@@ -159,9 +159,9 @@ See `src/backend/settings.py` for all configuration options. Key settings:
 | `AZURE_OPENAI_GPT_MODEL` | GPT model deployment name |
 | `AZURE_OPENAI_GPT_IMAGE_ENDPOINT` | Azure OpenAI endpoint for GPT image model (if separate) |
 | `AZURE_OPENAI_IMAGE_MODEL` | GPT image model deployment name (gpt-image-1-mini) |
-| `COSMOS_ENDPOINT` | Azure Cosmos DB endpoint |
-| `COSMOS_DATABASE` | Cosmos DB database name |
-| `AZURE_STORAGE_ACCOUNT_NAME` | Storage account name |
+| `AZURE_COSMOS_ENDPOINT` | Azure Cosmos DB endpoint |
+| `AZURE_COSMOS_DATABASE_NAME` | Cosmos DB database name |
+| `AZURE_BLOB_ACCOUNT_NAME` | Storage account name |
 | `BRAND_*` | Brand guideline parameters |
 
 ### Brand Guidelines