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‎docs/LOCAL_DEPLOYMENT.md‎

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‎docs/LocalDevelopmentSetup.md‎

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‎docs/azure_account_setup.md‎

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## Azure account setup
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1. Sign up for a [free Azure account](https://azure.microsoft.com/free/) and create an Azure Subscription.
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2. Check that you have the necessary permissions:
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* Your Azure account must have `Microsoft.Authorization/roleAssignments/write` permissions, such as [Role Based Access Control Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#role-based-access-control-administrator-preview), [User Access Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#user-access-administrator), or [Owner](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#owner).
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* Your Azure account also needs `Microsoft.Resources/deployments/write` permissions on the subscription level.
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You can view the permissions for your account and subscription by following the steps below:
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- Navigate to the [Azure Portal](https://portal.azure.com/) and click on `Subscriptions` under 'Navigation'
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- Select the subscription you are using for this accelerator from the list.
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- If you try to search for your subscription and it does not come up, make sure no filters are selected.
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- Select `Access control (IAM)` and you can see the roles that are assigned to your account for this subscription.
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- If you want to see more information about the roles, you can go to the `Role assignments`
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tab and search by your account name and then click the role you want to view more information about.

‎docs/azure_openai_model_quota_settings.md‎

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## How to Check & Update Quota
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Please follow [quota check instructions guide](./QuotaCheck.md) to check quota availability by region.
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1. **Navigate** to the [Azure AI Foundry portal](https://ai.azure.com/).
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2. **Click** on view all resources and **Search** for OpenAI resource associated with this accelerator.
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3. **Go to** the `Shared Resources` section in the bottom-left navigation menu.
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4. Select `Quota`
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- Click on the `GlobalStandard` dropdown.
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- Select the required **GPT model** (`gpt-4.1` or `text-embedding-ada-002`).
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- Choose the **region** where the deployment is hosted.
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5. Request More Quota or delete any unused model deployments as needed.

‎docs/customizing_azd_parameters.md‎

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# Customizing Azure Deployment Parameters
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By default this template will use the environment name as the prefix to prevent naming collisions within Azure. The parameters below show the default values. You only need to run the statements below if you need to change the values.
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> To override any of the parameters, run `azd env set <PARAMETER_NAME> <VALUE>` before running `azd up`. On the first azd command, it will prompt you for the environment name. Be sure to choose 3-16 characters alphanumeric unique name.
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## Core Configuration Parameters
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| **Name** | **Type** | **Default Value** | **Purpose** |
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|----------|----------|-------------------|-------------|
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| `AZURE_ENV_NAME` | string | (prompted) | Sets the environment name prefix for all Azure resources (3-16 alphanumeric characters) |
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| `AZURE_LOCATION` | string | (prompted) | Sets the primary location/region for all Azure resources |
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| `APP_ENV` | string | `Prod` | Application environment (Prod, Dev, etc.) |
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## Application Hosting Parameters
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| **Name** | **Type** | **Default Value** | **Purpose** |
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|----------|----------|-------------------|-------------|
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| `AZURE_APP_SERVICE_HOSTING_MODEL` | string | `container` | Hosting model for web apps (container or code) |
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| `HOSTING_PLAN_SKU` | string | `B3` | App Service plan pricing tier (B2, B3, S1, S2) |
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## Database Configuration
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| **Name** | **Type** | **Default Value** | **Purpose** |
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|----------|----------|-------------------|-------------|
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| `DATABASE_TYPE` | string | `PostgreSQL` | Type of database to deploy (PostgreSQL or CosmosDB) |
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## Azure AI Configurations
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| **Name** | **Type** | **Default Value** | **Purpose** |
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|----------|----------|-------------------|-------------|
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| `AZURE_SEARCH_USE_INTEGRATED_VECTORIZATION` | boolean | `false` | Enable integrated vectorization (must be false for PostgreSQL) |
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| `AZURE_SEARCH_USE_SEMANTIC_SEARCH` | boolean | `false` | Enable semantic search capabilities |
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| `AZURE_OPENAI_SKU_NAME` | string | `S0` | Azure OpenAI resource SKU |
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| `AZURE_OPENAI_MODEL` | string | `gpt-4.1` | Model deployment name |
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| `AZURE_OPENAI_MODEL_NAME` | string | `gpt-4.1` | Actual model name |
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| `AZURE_OPENAI_MODEL_VERSION` | string | `2025-04-14` | Model version |
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| `AZURE_OPENAI_MODEL_CAPACITY` | integer | `150` | Model capacity (TPM in thousands) |
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| `AZURE_OPENAI_API_VERSION` | string | `2024-02-01` | Azure OpenAI API version |
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| `AZURE_OPENAI_STREAM` | boolean | `true` | Enable streaming responses |
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| `AZURE_OPENAI_EMBEDDING_MODEL` | string | `text-embedding-ada-002` | Embedding model deployment name |
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| `AZURE_OPENAI_EMBEDDING_MODEL_NAME` | string | `text-embedding-ada-002` | Actual embedding model name |
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| `AZURE_OPENAI_EMBEDDING_MODEL_VERSION` | string | `2` | Embedding model version |
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| `AZURE_OPENAI_EMBEDDING_MODEL_CAPACITY` | integer | `100` | Embedding model capacity (TPM in thousands) |
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| `USE_ADVANCED_IMAGE_PROCESSING` | boolean | `false` | Enable vision LLM and Computer Vision for images (must be false for PostgreSQL) |
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| `ADVANCED_IMAGE_PROCESSING_MAX_IMAGES` | integer | `1` | Maximum images per vision model request |
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| `AZURE_OPENAI_VISION_MODEL` | string | `gpt-4.1` | Vision model deployment name |
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| `AZURE_OPENAI_VISION_MODEL_NAME` | string | `gpt-4.1` | Actual vision model name |
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| `AZURE_OPENAI_VISION_MODEL_VERSION` | string | `2025-04-14` | Vision model version |
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| `AZURE_OPENAI_VISION_MODEL_CAPACITY` | integer | `10` | Vision model capacity (TPM in thousands) |
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| `AZURE_COMPUTER_VISION_LOCATION` | string | (empty) | Location for Computer Vision resource |
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| `COMPUTER_VISION_SKU_NAME` | string | `S1` | Computer Vision SKU (F0 or S1) |
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| `AZURE_COMPUTER_VISION_VECTORIZE_IMAGE_API_VERSION` | string | `2024-02-01` | API version for image vectorization |
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| `AZURE_COMPUTER_VISION_VECTORIZE_IMAGE_MODEL_VERSION` | string | `2023-04-15` | Model version for image vectorization |
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| `AZURE_SPEECH_RECOGNIZER_LANGUAGES` | string | `en-US,fr-FR,de-DE,it-IT` | Comma-separated list of speech recognition languages |
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## Virtual Machine Configuration (Production Only)
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| **Name** | **Type** | **Default Value** | **Purpose** |
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|----------|----------|-------------------|-------------|
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| `AZURE_ENV_JUMPBOX_SIZE` | string | (empty) | Size of the jump box VM |
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| `AZURE_ENV_VM_ADMIN_USERNAME` | string | (auto-generated) | Administrator username for VMs |
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| `AZURE_ENV_VM_ADMIN_PASSWORD` | string | (auto-generated) | Administrator password for VMs |
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## How to Set a Parameter
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To customize any of the above values, run the following command **before** `azd up`:
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```bash
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azd env set <PARAMETER_NAME> <VALUE>
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```
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### Examples
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**Set a custom Azure region:**
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```bash
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azd env set AZURE_LOCATION eastus2
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```
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**Configure Azure OpenAI model capacity:**
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```bash
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azd env set AZURE_OPENAI_MODEL_CAPACITY 200
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azd env set AZURE_OPENAI_EMBEDDING_MODEL_CAPACITY 150
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```
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## Important Notes
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1. **PostgreSQL Limitations**: When using `DATABASE_TYPE=PostgreSQL`, you must set:
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- `AZURE_SEARCH_USE_INTEGRATED_VECTORIZATION=false`
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- `USE_ADVANCED_IMAGE_PROCESSING=false`
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- `ORCHESTRATION_STRATEGY=semantic_kernel` (recommended)
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2. **Region Compatibility**: Not all services are available in all regions. Verify service availability in your chosen region before deployment.

‎docs/delete_resource_group.md‎

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# Deleting Resources After a Failed Deployment in Azure Portal
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If your deployment fails and you need to clean up the resources manually, follow these steps in the Azure Portal.
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---
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## **1. Navigate to the Azure Portal**
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1. Open [Azure Portal](https://portal.azure.com/).
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2. Sign in with your Azure account.
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---
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## **2. Find the Resource Group**
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1. In the search bar at the top, type **"Resource groups"** and select it.
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2. Locate the **resource group** associated with the failed deployment.
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![Resource Groups](./images/resourcegroup.png)
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![Resource Groups](./images/resource-groups.png)
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---
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## **3. Delete the Resource Group**
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1. Click on the **resource group name** to open it.
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2. Click the **Delete resource group** button at the top.
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![Delete Resource Group](./images/DeleteRG.png)
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3. Type the resource group name in the confirmation box and click **Delete**.
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📌 **Note:** Deleting a resource group will remove all resources inside it.
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---
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## **4. Delete Individual Resources (If Needed)**
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If you don’t want to delete the entire resource group, follow these steps:
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1. Open **Azure Portal** and go to the **Resource groups** section.
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2. Click on the specific **resource group**.
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3. Select the **resource** you want to delete (e.g., App Service, Storage Account).
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4. Click **Delete** at the top.
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![Delete Individual Resource](./images/deleteservices.png)
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---
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## **5. Verify Deletion**
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- After a few minutes, refresh the **Resource groups** page.
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- Ensure the deleted resource or group no longer appears.
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📌 **Tip:** If a resource fails to delete, check if it's **locked** under the **Locks** section and remove the lock.

‎docs/images/DeleteRG.png‎

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‎docs/images/deleteservices.png‎

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‎docs/images/resource-groups.png‎

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‎docs/images/resourcegroup.png‎

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