Enable system-assigned managed identity support for existing Foundry projects and add documentation for reusing existing Azure AI Foundry project

Author: Prasanjeet-Microsoft

docs/DeploymentGuide.md

@@ -153,7 +153,8 @@ When you start the deployment, most parameters will have **default values**, but
 | **GPT Model Capacity**          | Sets the GPT model capacity.                                 | 150        |
 | **Image Tag**                  | Docker image tag used for container deployments.                                    | latest            |
 | **Enable Telemetry**           | Enables telemetry for monitoring and diagnostics.                                    | true              |
-
+| **Existing Log Analytics Workspace**        | To reuse an existing Log Analytics Workspace ID instead of creating a new one.              | *(none)*          |
+| **Existing Azure AI Foundry Project**        | To reuse an existing Azure AI Foundry Project ID instead of creating a new one.              | *(none)*          |
 
 </details>
 
@@ -176,6 +177,14 @@ To adjust quota settings, follow these [steps](./AzureGPTQuotaSettings.md).
 
 </details>
 
+<details>
+
+  <summary><b>Reusing an Existing Azure AI Foundry Project</b></summary>
+
+  Guide to get your [Existing Project ID](/docs/re-use-foundry-project.md)
+
+</details>
+
 ### Deploying with AZD
 
 Once you've opened the project in [Codespaces](#github-codespaces), [Dev Containers](#vs-code-dev-containers), or [locally](#local-environment), you can deploy it to Azure by following these steps:

docs/images/re_use_foundry_project/azure_ai_foundry_list.png

@@ -0,0 +1,44 @@
+[← Back to *DEPLOYMENT* guide](/docs/DeploymentGuide.md#deployment-options--steps)
+
+# Reusing an Existing Azure AI Foundry Project
+To configure your environment to use an existing Azure AI Foundry Project, follow these steps:
+---
+### 1. Go to Azure Portal
+Go to https://portal.azure.com
+
+### 2. Search for Azure AI Foundry
+In the search bar at the top, type "Azure AI Foundry" and click on it. Then select the Foundry service instance where your project exists.
+
+![alt text](../docs/images/re_use_foundry_project/azure_ai_foundry_list.png)
+
+### 3. Navigate to Projects under Resource Management
+On the left sidebar of the Foundry service blade:
+
+- Expand the Resource Management section
+- Click on Projects (this refers to the active Foundry project tied to the service)
+
+### 4. Click on the Project
+From the Projects view: Click on the project name to open its details
+
+    Note: You will see only one project listed here, as each Foundry service maps to a single project in this accelerator
+
+![alt text](../docs/images/re_use_foundry_project/navigate_to_projects.png)
+
+### 5. Copy Resource ID
+In the left-hand menu of the project blade: 
+
+- Click on Properties under Resource Management
+- Locate the Resource ID field
+- Click on the copy icon next to the Resource ID value
+
+![alt text](../docs/images/re_use_foundry_project/project_resource_id.png)
+
+### 6. Set the Foundry Project Resource ID in Your Environment
+Run the following command in your terminal
+```bash
+azd env set AZURE_ENV_FOUNDRY_PROJECT_ID '<Existing Foundry Project Resource ID>'
+```
+Replace `<Existing Foundry Project Resource ID>` with the value obtained from Step 5.
+
+### 7. Continue Deployment
+Proceed with the next steps in the [deployment guide](/docs/DeploymentGuide.md#deployment-options--steps).

docs/images/re_use_foundry_project/navigate_to_projects.png

@@ -277,7 +277,7 @@ module existing_cognigive_service_dependencies 'modules/dependencies.bicep' = if
     projectName: projectName
     projectDescription: projectDescription
     azureExistingAIProjectResourceId: existingFoundryProjectResourceId
-    location: location
+    location: cognitiveServiceExisting.?location!
     deployments: deployments
     diagnosticSettings: diagnosticSettings
     lock: lock
@@ -311,8 +311,8 @@ output endpoint string = useExistingService ? cognitiveServiceExisting.propertie
 output endpoints endpointType = useExistingService ? cognitiveServiceExisting.properties.endpoints : cognitiveService.properties.endpoints
 
 @description('The principal ID of the system assigned identity.')
-output systemAssignedMIPrincipalId string? = useExistingService ? cognitiveServiceExisting.identity.principalId : cognitiveService.?identity.?principalId
- 
+output systemAssignedMIPrincipalId string? = useExistingService ? cognitiveServiceExisting.?identity.?principalId : cognitiveService.?identity.?principalId
+
 @description('The location the resource was deployed into.')
 output location string = useExistingService ? cognitiveServiceExisting.location : cognitiveService.location
 

docs/images/re_use_foundry_project/project_resource_id.png

@@ -23,8 +23,8 @@ param name string
 ])
 param sku string = 'S0'
 
-@description('Optional. Location for all Resources.')
-param location string = resourceGroup().location
+@description('Optional. Location for Cognitive Services.')
+param location string
 
 @description('Optional. Tags of the resource.')
 param tags object?

docs/re-use-foundry-project.md

@@ -2,7 +2,7 @@
 param name string
 
 @description('Required. The location of the Project resource.')
-param location string = resourceGroup().location
+param location string
 
 @description('Optional. The description of the AI Foundry project to create. Defaults to the project name.')
 param desc string = name
@@ -40,11 +40,19 @@ resource aiProject 'Microsoft.CognitiveServices/accounts/projects@2025-04-01-pre
   }
 }
 
+// Assign identity to existing project
+resource existingProject 'Microsoft.CognitiveServices/accounts/projects@2025-04-01-preview' = if (useExistingProject && !empty(existingProjName)) {
+  name: existingProjName
+  parent: cogServiceReference
+  location: location
+  identity: { type: 'SystemAssigned' }
+}
+
 @description('AI Project metadata including name, resource ID, and API endpoint.')
 output aiProjectInfo aiProjectOutputType = {
-  name: useExistingProject ? existingProjName : aiProject.name
-  resourceId: useExistingProject ? azureExistingAIProjectResourceId : aiProject.id
-  apiEndpoint: useExistingProject ? existingProjEndpoint : aiProject.properties.endpoints['AI Foundry API']
+  name: useExistingProject ? existingProject.name : aiProject.name
+  resourceId: useExistingProject ? existingProject.id : aiProject.id
+  apiEndpoint: useExistingProject ? existingProject.properties.endpoints['AI Foundry API'] : aiProject.properties.endpoints['AI Foundry API']
 }
 
 @export()