Add azd-based deployment Infrastructure (#63) #24
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* Add azd infrastructure for easy deployment of healthcare AI models • Complete Bicep infrastructure for fresh and existing Azure ML workspace deployments • Optional GPT model integration with Azure AI Services and AI Hub connections • Automated model endpoint deployment with configurable instance types and scaling • Comprehensive deployment guides and README documentation for both deployment types • Python automation scripts for model selection, environment setup, and cleanup operations * Refactor deployment scripts and documentation - Removed the README.md file from the deploy directory as it was redundant. - Updated existing README.md files to reference the main deployment guide for GPT model configuration and model selection. - Enhanced the setup script for existing deployments to clarify cleanup procedures. - Improved resource cleanup instructions in both fresh and existing deployment README.md files. - Introduced a new cleanup script to handle resource deletion for existing deployments, replacing the previous delete_endpoints.py script. - Updated Bicep templates to include tagging for resources. - Added utility functions for detecting deployment types and improved error handling in cleanup scripts. * address comments and add endpoint testing CLI to check environment - Add healthcareai-test command for testing model endpoint connectivity - Include AZURE_OPENAI_MODEL_NAME in deployment configuration and environment setup - Update clients and examples to use centralized settings for OpenAI integration - Improve security and response handling in model clients - Update deployment documentation with better navigation and Azure ML compute instance instructions * remove aihub dependency * disable shared access key for fresh deployment * fix lint * update readme with deployment quickstarts and better env setup * update permissions documentation, clean up empty files. * minor edits * update README and deployment scripts --------- Co-authored-by: Jameson Merkow <[email protected]>
matthiasblondeel
approved these changes
Jul 14, 2025
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• Complete Bicep infrastructure for fresh and existing Azure ML workspace deployments
• Optional GPT model integration
• Automated model endpoint deployment with configurable instance types and scaling
• Comprehensive deployment guides and README documentation for all deployment types
• Python automation scripts for model selection, environment setup, and cleanup operations