chore: Reuse existing AIFoundry project#151
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Shreyas-Microsoft wants to merge 7 commits intomainfrom
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| @description('Optional. Use this parameter to use an existing AI project resource ID') | ||
| param azureExistingAIProjectResourceId string? | ||
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When we are reusing existing project we should not create cognitive service account as well. We should use the existing cognitive service resource itself.
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Purpose
This pull request introduces functionality to support the reuse of existing AI project resources in Azure deployments. The changes primarily involve updating Bicep templates to enable conditional handling of existing AI project resource IDs, ensuring compatibility with projects across different resource groups. Below are the most important changes grouped by theme:
Parameter Additions and Updates
azureExistingAIProjectResourceIdininfra/main.bicepandinfra/modules/ai-foundry/main.bicepto allow specifying an existing AI project resource ID. This parameter is optional and supports reuse of resources across different resource groups. [1] [2]infra/main.parameters.jsonto include the new parameterazureExistingAIProjectResourceIdfor configuration.Conditional Logic for Resource Handling
infra/modules/ai-foundry/project.bicepto extract components (e.g., project name, subscription ID) from the existing AI project resource ID and determine whether to use an existing project or create a new one.cogServiceReference,aiProject) to conditionally create new AI projects only when theazureExistingAIProjectResourceIdparameter is not provided.Role Assignments for AI Projects
newProjectRoleAssignmentsfor new AI projects.existingProjectRoleAssignmentsfor existing AI projects from different resource groups. This ensures proper role assignment and telemetry handling. (F9f1e137L69R96, infra/modules/ai-foundry/project.bicepR99-R122)Output Adjustments
name,resourceId,apiEndpoint) ininfra/modules/ai-foundry/project.bicepto dynamically reflect whether a new AI project is created or an existing one is reused.These changes enhance flexibility in Azure deployments, allowing teams to integrate existing AI projects seamlessly while maintaining robust role assignment and telemetry support.
Does this introduce a breaking change?
Golden Path Validation
Deployment Validation
What to Check
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Other Information