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Merge pull request #459 from microsoft/psl-us18810-docgen
feat: Standardize Bicep Parameters for DocGen
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‎docs/CustomizingAzdParameters.md‎

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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 <key> <value>` before running `azd up`. On the first azd command, it will prompt you for the environment name. Be sure to choose 3-20 charaters alphanumeric unique name.
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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 3-20 charaters alphanumeric unique name.
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## Parameters
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Change the Secondary Location (example: eastus2, westus2, etc.)
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| Name | Type | Example Value | Purpose |
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| -------------------------------------- | ------- | ---------------------------- | ----------------------------------------------------------------------------- |
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| `AZURE_LOCATION` | string | `japaneast` | Sets the Azure region for resource deployment. |
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| `AZURE_ENV_NAME` | string | `docgen` | Sets the environment name prefix for all Azure resources. |
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| `AZURE_ENV_SECONDARY_LOCATION` | string | `eastus2` | Specifies a secondary Azure region. |
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| `AZURE_ENV_MODEL_DEPLOYMENT_TYPE` | string | `Standard` | Defines the model deployment type (allowed: `Standard`, `GlobalStandard`). |
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| `AZURE_ENV_MODEL_NAME` | string | `gpt-4o` | Specifies the GPT model name (allowed: `gpt-4`, `gpt-4o`). |
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| `AZURE_ENV_MODEL_VERSION` | string | `2024-05-13` | Set the Azure model version (allowed values: `2024-08-06`). |
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| `AZURE_ENV_OPENAI_API_VERSION` | string | `2024-05-01-preview` | Specifies the API version for Azure OpenAI. |
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| `AZURE_ENV_MODEL_CAPACITY` | integer | `30` | Sets the GPT model capacity (based on what's available in your subscription). |
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| `AZURE_ENV_EMBEDDING_MODEL_NAME` | string | `text-embedding-ada-002` | Sets the name of the embedding model to use. |
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| `AZURE_ENV_IMAGETAG` | string | `latest` | Set the Image tag Like (allowed values: latest, dev, hotfix) |
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| `AZURE_ENV_EMBEDDING_MODEL_CAPACITY` | integer | `80` | Sets the capacity for the embedding model deployment. |
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| `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID` | string | `<Existing Workspace Id>` | Reuses an existing Log Analytics Workspace instead of creating a new one. |
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```shell
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azd env set AZURE_ENV_SECONDARY_LOCATION eastus2
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```
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Change the Model Deployment Type (allowed values: Standard, GlobalStandard)
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```shell
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azd env set AZURE_ENV_MODEL_DEPLOYMENT_TYPE Standard
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```
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Set the Model Name (allowed values: gpt-4, gpt-4o)
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```shell
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azd env set AZURE_ENV_MODEL_NAME gpt-4o
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```
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## How to Set a Parameter
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Change the Model Capacity (choose a number based on available GPT model capacity in your subscription)
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To customize any of the above values, run the following command **before** `azd up`:
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```shell
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azd env set AZURE_ENV_MODEL_CAPACITY 30
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```bash
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azd env set <PARAMETER_NAME> <VALUE>
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```
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Change the Embedding Model
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```shell
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azd env set AZURE_ENV_EMBEDDING_MODEL_NAME text-embedding-ada-002
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```
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Change the Embedding Deployment Capacity (choose a number based on available embedding model capacity in your subscription)
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```shell
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azd env set AZURE_ENV_EMBEDDING_MODEL_CAPACITY 80
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```
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**Example:**
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Set the Log Analytics Workspace Id if you need to reuse the existing workspace
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```shell
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azd env set AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID '<Existing Log Analytics Workspace Id>'
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```bash
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azd env set AZURE_LOCATION westus2
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```

‎docs/DeploymentGuide.md‎

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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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## Deployment Options & Steps
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Pick from the options below to see step-by-step instructions for GitHub Codespaces, VS Code Dev Containers, and Local Environments.
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<details>
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<summary><b>Configurable Deployment Settings</b></summary>
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When you start the deployment, most parameters will have **default values**, but you can update the following settings:
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| **Setting** | **Description** | **Default value** |
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|------------|----------------| ------------|
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| **Azure Region** | The region where resources will be created. | eastus |
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| **Environment Name** | A **3-20 character alphanumeric value** used to generate a unique ID to prefix the resources. | byctemplate |
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| **Secondary Location** | A **less busy** region for **CosmosDB**, useful in case of availability constraints. | eastus2 |
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| **Deployment Type** | Select from a drop-down list. | Global Standard |
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| **GPT Model** | Choose from **gpt-4, gpt-4o** | gpt-4o |
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| **GPT Model Deployment Capacity** | Configure capacity for **GPT models**. | 30k |
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| **Embedding Model** | Default: **text-embedding-ada-002**. | text-embedding-ada-002 |
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| **Embedding Model Capacity** | Set the capacity for **embedding models**. | 80k |
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| **Existing Log analytics workspace** | To reuse the existing Log analytics workspace Id. | |
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When you start the deployment, most parameters will have **default values**, but you can update the following settings:[here](../docs/CustomizingAzdParameters.md):
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| **Setting** | **Description** | **Default Value** |
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| ------------------------------------ | --------------------------------------------------------------------------------------------- | ------------------------ |
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| **Azure Region** | The region where resources will be created. | `eastus` |
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| **Environment Name** | A **3–20 character alphanumeric** value used to generate a unique ID to prefix the resources. | `byctemplate` |
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| **Secondary Location** | A **less busy** region for **CosmosDB**, useful in case of availability constraints. | `eastus2` |
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| **Deployment Type** | Model deployment type (allowed: `Standard`, `GlobalStandard`). | `GlobalStandard` |
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| **GPT Model** | Choose from **gpt-4**, **gpt-4o**. | `gpt-4o` |
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| **GPT Model Version** | Version of the GPT model to use (e.g., `2024-08-06`). | `2024-05-13` |
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| **OpenAI API Version** | Azure OpenAI API version used for deployments. | `2024-05-01-preview` |
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| **GPT Model Deployment Capacity** | Configure the capacity for **GPT model deployments** (in thousands). | `30k` |
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| **Embedding Model** | The embedding model used by the app. | `text-embedding-ada-002` |
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| **Embedding Model Capacity** | Configure the capacity for **embedding model deployments** (in thousands). | `80k` |
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| **Image Tag** | Image version for deployment (allowed: `latest`, `dev`, `hotfix`). | `latest` |
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| **Existing Log Analytics Workspace** | If reusing a Log Analytics Workspace, specify the ID. | *(none)* |
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</details>
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‎infra/main.bicepparam‎

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param deploymentType = readEnvironmentVariable('AZURE_ENV_MODEL_DEPLOYMENT_TYPE', 'GlobalStandard')
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param gptModelName = readEnvironmentVariable('AZURE_ENV_MODEL_NAME', 'gpt-4o')
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param gptModelVersion = readEnvironmentVariable('AZURE_ENV_MODEL_VERSION', '2024-05-13')
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param azureOpenaiAPIVersion = readEnvironmentVariable('AZURE_ENV_OPENAI_API_VERSION', '2024-05-01-preview')
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param gptDeploymentCapacity = int(readEnvironmentVariable('AZURE_ENV_MODEL_CAPACITY', '30'))
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param embeddingModel = readEnvironmentVariable('AZURE_ENV_EMBEDDING_MODEL_NAME', 'text-embedding-ada-002')
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param imageTag = readEnvironmentVariable('AZURE_ENV_IMAGETAG', 'latest')
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param embeddingDeploymentCapacity = int(readEnvironmentVariable('AZURE_ENV_EMBEDDING_MODEL_CAPACITY', '80'))
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param existingLogAnalyticsWorkspaceId = readEnvironmentVariable('AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID', '')

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