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Purpose

This pull request adds several new documentation files and updates existing configuration to improve deployment guidance, resource cleanup, quota management, and environment configuration for the document knowledge mining solution accelerator. The main focus is on providing clear, step-by-step instructions for post-deployment tasks, quota adjustments, resource deletion, and reusing existing Azure resources.

Deployment and Post-Deployment Guidance:

  • Added a comprehensive post-deployment configuration guide (docs/PostDeploymentConfiguration.md) detailing how to run deployment scripts, configure model quotas, and manually set up content filters and rate limits for Azure OpenAI models.
  • Added instructions for reusing an existing Log Analytics Workspace during deployment, including how to locate the resource and set the environment variable. (docs/re-use-log-analytics.md)

Resource and Quota Management:

  • Added a step-by-step guide for checking and updating AI model quotas in Azure, including links to relevant portals and instructions for requesting quota increases or cleaning up unused deployments. (docs/AzureAIModelQuotaSettings.md)

Resource Cleanup Procedures:

  • Added detailed instructions for deleting Azure resource groups and individual resources after a failed deployment, including troubleshooting tips for locked resources. (docs/DeleteResourceGroup.md)

Configuration File Update:

  • Commented out the metadata section in the azure.yaml configuration file, possibly to address a deployment or template issue. (azure.yaml)

Does this introduce a breaking change?

  • Yes
  • No

Golden Path Validation

Not Required.

Deployment Validation

Not Required.

What to Check

Verify that the following are valid
Thoroughly verify the Deployment Guide

Other Information

N/A

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3 participants