Merge remote-tracking branch 'origin/main' into fix/ai-search-role-assign

Author: Prajwal-Microsoft

azure.yaml

@@ -14,15 +14,4 @@ hooks:
       shell: sh
       run: chmod u+r+x ./scripts/set_conns_env_vars.sh; ./scripts/set_conns_env_vars.sh
       interactive: true
-      continueOnError: false
-  preprovision:
-    posix:
-      shell: sh
-      run: chmod u+r+x ./scripts/validate_model_deployment_quotas.sh; chmod u+r+x ./scripts/validate_model_quota.sh; ./scripts/validate_model_deployment_quotas.sh --subscription $AZURE_SUBSCRIPTION_ID --location $AZURE_LOCATION --models-parameter "aiModelDeployments"
-      interactive: false
-      continueOnError: false
-    windows:
-      shell: pwsh
-      run: ./scripts/validate_model_deployment_quotas.ps1 -Subscription $env:AZURE_SUBSCRIPTION_ID -Location $env:AZURE_LOCATION -ModelsParameter "aiModelDeployments"
-      interactive: false
       continueOnError: false

docs/modify_deployed_models.md

@@ -1,37 +1,24 @@
 ## Update AI Model Deployments
-The AI Models that can be deployed and attached to the Foundry hub can be modified by changing the parameters within the [main.parameters.json](../infra/main.parameters.json) file.
 
-By modifying the parameters listed in the parameters.json 'aiModelDeployments' section, additional or different models can be deployed with the solution and ready for use after the deployment. Simply modify the values to your liking in each of the objects, or add additional objects to the array. 
-```powershell
+The AI Models that can be deployed and attached to the Foundry hub can be modified by changing the parameters within the [main.parameters.json](../infra/main.parameters.json) file.
 
+By modifying the parameters `aiEmbeddingModelDeployment` and `aiGPTModelDeployment`  listed in the parameters.json, different embedding and GPT models can be deployed with the solution and ready for use after the deployment. Simply modify the values to your liking in each of the objects.
 
-    "aiModelDeployments": {
-      "value": [
-        {
-          "name": "textembed",
-          "model": {
-            "name": modelName,
-            "format": modelPublisherFormat,
-            "version": modelVersion
-          },
-          "sku": {
-            "name": skuName,
-            "capacity": capacity
-          }
-        },
-        {
-          "name": "gpt",
-          "model": {
-            "name": "gpt-4o",
-            "version": "2024-05-13",
-            "format": "OpenAI"
-          },
-          "sku": {
-            "name": "GlobalStandard",
-            "capacity": 10
-          }
-        }
-      ]
+```powershell
+    "aiEmbeddingModelDeployment": {
+      "value": {
+        "modelName": modelName,
+        "version": modelVersion,
+        "capacity": capacity
+      }
+    },
+    "aiGPTModelDeployment": {
+      "value": {
+        "modelName": "gpt-4o",
+        "version": "2024-05-13",
+        "capacity": 150
+      }
     }
 ```
+
 To find and validate additional model information, the [AI Foundry](https://ai.azure.com/explore/models) model page has the above parameters to refer to, as does the Microsoft Learn page for [Azure OpenAI Service Models](https://learn.microsoft.com/en-us/azure/ai-services/openai_) information.

infra/main.bicep

@@ -5,11 +5,27 @@ targetScope = 'resourceGroup'
 @description('The name of the environment/application. Use alphanumeric characters only.')
 param name string
 
-@description('Specifies the location for all the Azure resources. Defaults to the location of the resource group.')
+@metadata({ azd: { type: 'location' } })
+@description('Specifies the location for all the Azure resources.')
 param location string
 
-@description('Optional. Specifies the OpenAI deployments to create.')
-param aiModelDeployments deploymentsType[] = []
+@description('Specifies the AI embedding model to use for the AI Foundry deployment. This is the model used for text embeddings in AI Foundry. NOTE: Any adjustments to this parameter\'s values must also be made on the aiDeploymentsLocation metadata in the main.bicep file.') 
+param aiEmbeddingModelDeployment modelDeploymentType
+
+@description('Specifies the AI chat model to use for the AI Foundry deployment. This is the model used for chat interactions in AI Foundry. NOTE: Any adjustments to this parameter\'s values must also be made on the aiDeploymentsLocation metadata in the main.bicep file.')
+param aiGPTModelDeployment modelDeploymentType
+
+@metadata({
+  azd: {
+    type: 'location'
+    usageName: [
+      'OpenAI.GlobalStandard.gpt-4o,150'
+      'OpenAI.GlobalStandard.text-embedding-3-small,100'
+    ]
+  }
+})
+@description('Required. Location for AI Foundry deployment. This is the location where the AI Foundry resources will be deployed.')
+param aiDeploymentsLocation string
 
 @description('Specifies whether creating an Azure Container Registry.')
 param acrEnabled bool = false
@@ -83,12 +99,6 @@ param documentIntelligenceEnabled bool = false
 param networkAcls object ={
   defaultAction: 'Deny'
   bypass: 'AzureServices' // ✅ Allows trusted Microsoft services
-  // virtualNetworkRules: [
-  //   {
-  //     id: networkIsolation ? network.outputs.vmSubnetName : ''
-  //     ignoreMissingVnetServiceEndpoint: true
-  //   }
-  // ]
 }
 
 @description('Name of the first project')
@@ -216,13 +226,26 @@ module cognitiveServices 'modules/cognitive-services/main.bicep' = {
   params: {
     name: name
     resourceToken: resourceToken
-    location: location
+    location: aiDeploymentsLocation
     networkIsolation: networkIsolation
     networkAcls: networkAcls
     virtualNetworkResourceId: networkIsolation ? network.outputs.virtualNetworkId : ''
     virtualNetworkSubnetResourceId: networkIsolation ? network.outputs.vmSubnetId : ''
     logAnalyticsWorkspaceResourceId: logAnalyticsWorkspace.outputs.resourceId
-    aiModelDeployments: aiModelDeployments
+    aiModelDeployments: [
+      for model in [aiEmbeddingModelDeployment, aiGPTModelDeployment]: {
+        name: empty(model.?name) ? model.modelName : model.?name
+        model: {
+          name: model.modelName
+          format: 'OpenAI'
+          version: model.version
+        }
+        sku: {
+          name: 'GlobalStandard'
+          capacity: model.capacity
+        }
+      }
+    ]
     userObjectId: userObjectId
     contentSafetyEnabled: contentSafetyEnabled
     visionEnabled: visionEnabled
@@ -242,7 +265,7 @@ module project 'modules/ai-foundry-project/main.bicep' = {
     cosmosDbEnabled: cosmosDbEnabled
     searchEnabled: searchEnabled
     name: projectName
-    location: location
+    location: aiDeploymentsLocation
     storageName: storageAccount.outputs.storageName
     aiServicesName: cognitiveServices.outputs.aiServicesName
     nameFormatted:  searchEnabled ? aiSearch.outputs.name : ''
@@ -361,7 +384,7 @@ module sqlServer 'modules/sqlServer.bicep' = if (sqlServerEnabled) {
   }
 }
 
-import { sqlDatabaseType, databasePropertyType, deploymentsType } from 'modules/customTypes.bicep'
+import { sqlDatabaseType, databasePropertyType, modelDeploymentType } from 'modules/customTypes.bicep'
 
 
 output AZURE_KEY_VAULT_NAME string = keyvault.outputs.name