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… scripts and configuration
…emove unused agent factory classes, streamline ChatService and HistoryService, and enhance SQLTool for better database interaction. Update API routes and configuration management for improved clarity and performance. Upgrade dependencies in requirements.txt for compatibility with new Azure SDK versions.
…gin, ChatService, HistoryService, and App - Removed test cases for deprecated agent factories in test_app.py. - Updated test cases in test_chat_with_data_plugin.py to reflect changes in the ChatWithDataPlugin implementation. - Refactored test cases in test_chat_service.py to remove dependencies on mock requests and streamline the setup. - Enhanced test_generate_title in test_history_service.py to utilize the new v2 agent framework. - Improved error handling tests in test_chat_service.py for rate limits and general exceptions. - Consolidated mock setups and assertions for clarity and maintainability.
…lation and access
…security in ChatService and HistoryService
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…steps in Deployment Guide
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…edge-Mining-Solution-Accelerator into km-agentframework-v2
…edge-Mining-Solution-Accelerator into km-agentframework-v2
- Updated 00_create_sample_data_files.py to improve CSV and JSON export functions, ensuring better error handling and code readability. - Modified 01_create_search_index.py to include additional whitespace for consistency. - Enhanced 03_cu_process_data_text.py by implementing asynchronous processing for embeddings and agent creation, improving performance and scalability. - Updated 04_cu_process_custom_data.py to streamline the search index creation process and improve error handling. - Adjusted requirements.txt to include new agent framework dependencies and ensure compatibility. - Enhanced process_sample_data.sh and run_create_index_scripts.sh to support new solution_name parameter for better configuration management.
…processing scripts
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docs: update Technical Architecture diagram
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… in agent creation script
fix: add agent creation scripts with retry logic and Azure re-authentication
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Purpose
This pull request introduces several updates to documentation and deployment scripts to support the integration of the Azure AI Agent Framework (AFV2), improve post-deployment guidance, and streamline agent creation and sample data processing workflows. The most important changes include updating image tags and references for AFV2 across deployment workflows, revising documentation to clarify agent creation steps, and updating script parameters for improved clarity and flexibility.
Deployment workflow updates:
latest_waftolatest_afv2in.github/workflows/deploy-KMGeneric.yml,.github/workflows/docker-build.yml, and.github/workflows/job-azure-deploy.ymlto align with Azure AI Agent Framework v2. [1] [2] [3] [4]AZURE_ENV_IMAGETAGindocuments/CustomizingAzdParameters.mdto uselatest_afv2as the default value.Documentation improvements for agent creation and post-deployment steps:
documents/AVMPostDeploymentGuide.mdto introduce explicit steps for creating and activating a Python virtual environment, agent creation (viarun_create_agents_scripts.sh), and sample data processing, with clearer ordering and instructions. [1] [2] [3] [4] [5]documents/DeploymentGuide.mdto add detailed instructions and parameter descriptions for running the agent creation script, and revised sample data processing script parameters to include the solution name. [1] [2] [3]documents/CustomizeData.mdanddocuments/AVMPostDeploymentGuide.mdto update script parameters for custom data processing, adding solution name and reordering arguments for clarity. [1] [2]Script and configuration updates:
azure.yamlandazure_custom.yamlto include instructions for running the agent creation script before sample data processing, improving user guidance for both Windows and POSIX environments. [1] [2] [3]Solution overview and security documentation changes:
README.mdto reference Azure AI Agent Framework in the solution overview and removed Azure Key Vault from the pricing and security sections, emphasizing Managed Identity for secure access. [1] [2] [3]Workshop requirements update:
semantic-kernel[azure]dependency indocs/workshop/docs/workshop/requirements.txtfrom version 1.28.0 to 1.40.0.Does this introduce a breaking change?
Golden Path Validation
Deployment Validation