Merge pull request #501 from microsoft/dev

feat: Merge the Azd Quota check changes and removed USE_LOCAL_BUILD from dev to main

Author: Roopan-Microsoft

azure.yaml

@@ -9,19 +9,6 @@ metadata:
   template: [email protected]
 
 hooks:
-  preprovision:
-    windows:
-      run: |
-        $timestamp = Get-Date -Format "yyyyMMdd-HHmmss"; $logFile = "azd_preprovision_$timestamp.log"; ./infra/scripts/docker-build.ps1 $env:AZURE_SUBSCRIPTION_ID $env:AZURE_ENV_NAME $env:AZURE_LOCATION $env:AZURE_RESOURCE_GROUP $env:USE_LOCAL_BUILD $env:AZURE_ENV_IMAGETAG *>&1 | Tee-Object -FilePath $logFile
-      shell: pwsh
-      continueOnError: false
-      interactive: true
-    posix:
-      run: |
-        timestamp=$(date +"%Y%m%d-%H%M%S"); logFile="azd_preprovision_$timestamp.log"; sed -i 's/\r$//' ./infra/scripts/docker-build.sh; ./infra/scripts/docker-build.sh "$AZURE_SUBSCRIPTION_ID" "$AZURE_ENV_NAME" "$AZURE_LOCATION" "$AZURE_RESOURCE_GROUP" "$USE_LOCAL_BUILD" "$AZURE_ENV_IMAGETAG" 2>&1 | tee "$logFile"
-      shell: sh
-      continueOnError: false
-      interactive: true
   postprovision:
     windows:
       run: |

documents/CustomizingAzdParameters.md

@@ -22,7 +22,6 @@ By default this template will use the environment name as the prefix to prevent
 | `AZURE_ENV_IMAGETAG`                      | string  | `latest`        | Sets the image tag (`latest`, `dev`, `hotfix`, etc.).   |
 | `AZURE_OPENAI_EMBEDDING_MODEL_CAPACITY`   | integer | `80`                     | Sets the capacity for the embedding model deployment.                      |
 | `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID`    | string  | `<Existing Workspace Id>`            | Reuses an existing Log Analytics Workspace instead of creating a new one.  |
-| `USE_LOCAL_BUILD`    | string  | `false`           | Indicates whether to use a local container build for deployment.  |
 | `AZURE_EXISTING_AI_PROJECT_RESOURCE_ID`    | string  | `<Existing AI Project resource Id>`            | Reuses an existing AIFoundry and AIFoundryProject instead of creating a new one.  |
 
 

documents/DeploymentGuide.md

@@ -170,33 +170,6 @@ Once you've opened the project in [Codespaces](#github-codespaces), [Dev Contain
 
 6. If you are done trying out the application, you can delete the resources by running `azd down`.
 
-### Publishing Local Build Container to Azure Container Registry
-
-If you need to rebuild the source code and push the updated container to the deployed Azure Container Registry, follow these steps:
-
-1. Set the environment variable `USE_LOCAL_BUILD` to `True`:
-
-   - **Linux/macOS**:
-     ```bash
-     export USE_LOCAL_BUILD=True
-     ```
-
-   - **Windows (PowerShell)**:
-     ```powershell
-     $env:USE_LOCAL_BUILD = $true
-     ```
-2. Run the `az login` command
-   ```bash
-   az login
-   ```
-
-3. Run the `azd up` command again to rebuild and push the updated container:
-   ```bash
-   azd up
-   ```
-
-This will rebuild the source code, package it into a container, and push it to the Azure Container Registry associated with your deployment.
-
 ## Post Deployment Steps
 
 1. **Add App Authentication**

infra/main.bicep

@@ -20,11 +20,11 @@ param azureExistingAIProjectResourceId string = ''
     type: 'location'
   }
 })
-param contentUnderstandingLocation string
+param contentUnderstandingLocation string = 'swedencentral'
 
 @minLength(1)
 @description('Secondary location for databases creation(example:eastus2):')
-param secondaryLocation string
+param secondaryLocation string = 'eastus2'
 
 @minLength(1)
 @description('GPT model deployment type:')
@@ -47,7 +47,7 @@ param azureOpenAIApiVersion string = '2025-01-01-preview'
 @description('Capacity of the GPT deployment:')
 // You can increase this, but capacity is limited per model/region, so you will get errors if you go over
 // https://learn.microsoft.com/en-us/azure/ai-services/openai/quotas-limits
-param gptDeploymentCapacity int = 30
+param gptDeploymentCapacity int = 150
 
 @minLength(1)
 @description('Name of the Text Embedding model to deploy:')
@@ -72,6 +72,20 @@ param useLocalBuild string = 'false'
 var useLocalBuildLower = toLower(useLocalBuild)
 
 var uniqueId = toLower(uniqueString(subscription().id, environmentName, solutionLocation))
+
+
+@metadata({
+  azd:{
+    type: 'location'
+    usageName: [
+      'OpenAI.GlobalStandard.gpt-4o-mini,150'
+      'OpenAI.Standard.text-embedding-ada-002,80'
+    ]
+  }
+})
+@description('Location for AI Foundry deployment. This is the location where the AI Foundry resources will be deployed.')
+param aiDeploymentsLocation string
+
 var solutionPrefix = 'km${padLeft(take(uniqueId, 12), 12, '0')}'
 
 var containerRegistryName = '${abbrs.containers.containerRegistry}${solutionPrefix}'
@@ -107,7 +121,7 @@ module aifoundry 'deploy_ai_foundry.bicep' = {
   name: 'deploy_ai_foundry'
   params: {
     solutionName: solutionPrefix
-    solutionLocation: solutionLocation
+    solutionLocation: aiDeploymentsLocation
     keyVaultName: kvault.outputs.keyvaultName
     cuLocation: contentUnderstandingLocation
     deploymentType: deploymentType

infra/main.bicepparam

@@ -0,0 +1,48 @@
+{
+  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentParameters.json#",
+  "contentVersion": "1.0.0.0",
+  "parameters": {
+    "environmentName": {
+      "value": "${AZURE_ENV_NAME}"
+    },
+    "AZURE_LOCATION": {
+      "value": "${AZURE_LOCATION}"
+    },
+    "contentUnderstandingLocation" :{
+      "value": "${AZURE_CONTENT_UNDERSTANDING_LOCATION}"
+    },
+    "secondaryLocation": {
+      "value": "${AZURE_SECONDARY_LOCATION}"
+    },
+    "deploymentType": {
+      "value": "${AZURE_OPENAI_MODEL_DEPLOYMENT_TYPE}"
+    },
+    "gptModelName": {
+      "value": "${AZURE_OPENAI_DEPLOYMENT_MODEL}"
+    },
+    "gptModelVersion": {
+      "value": "${AZURE_ENV_MODEL_VERSION}"
+    },
+    "azureOpenaiAPIVersion ": {
+      "value": "${AZURE_OPENAI_API_VERSION}"
+    },
+    "gptDeploymentCapacity": {
+      "value": "${AZURE_OPENAI_DEPLOYMENT_MODEL_CAPACITY}"
+    },
+    "embeddingModel": {
+      "value": "${AZURE_OPENAI_EMBEDDING_MODEL}"
+    },
+    "embeddingDeploymentCapacity": {
+      "value": "${AZURE_OPENAI_EMBEDDING_MODEL_CAPACITY}"
+    },
+    "imageTag": {
+      "value": "${AZURE_ENV_IMAGETAG}"
+    },
+    "existingLogAnalyticsWorkspaceId": {
+      "value": "${AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID}"
+    },
+    "azureExistingAIProjectResourceId": {
+      "value": "${AZURE_EXISTING_AI_PROJECT_RESOURCE_ID}"
+    }
+  }
+}