feat: Macae rfp agent framework #571
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Replaced semantic-kernel imports and dependencies with agent-framework in config, models, and utils. Updated pyproject.toml to add agent-framework and remove semantic-kernel. This refactor aligns the codebase with the new agent-framework library for agent and kernel functionality.
Migrate from semantic-kernel to agent-framework
fix: Dev v3 to main
Adds a comprehensive AVM post-deployment guide and refactors post-deployment scripts (PowerShell and Bash) to support both azd and ARM/Bicep deployments, including improved Azure subscription selection and output parsing. Updates FastAPI app to use a lifespan context for agent cleanup on shutdown. Refactors CosmosDB and config code for clarity and style. Updates workflow files for more flexible test and deployment handling. Introduces new frontend components and hooks for plan cancellation dialog and alert, and updates related styles and service logic.
Added agent-framework-core, agent-framework-azure-ai, agent-framework-copilotstudio, agent-framework-devui, agent-framework-mem0, and agent-framework-redis as dependencies from the Microsoft agent-framework repository. Updated azure-ai-agents to version 1.2.0b5 and upgraded aiohttp to 3.13.1.
Macae rfp af 101725
Replaced references to agent_framework with semantic_kernel in app_config.py and utils_kernel.py. Updated models in messages_kernel.py to use KernelBaseModel and Field from semantic_kernel.kernel_pydantic for consistency with the new package structure.
Macae rfp af 101725
Deleted the websocket_streaming.py module and removed the create_kernel method from AppConfig, as the system now uses Azure AI Agent Project pattern. Added placeholder files for messages_af.py and utils_af.py to support future Azure Foundry integration.
fix: dev-v3 to main branch merge
Introduces new Pydantic-based data models in messages_af.py to replace KernelBaseModel from semantic_kernel. All original model names and structures are preserved to support incremental migration from the previous framework.
Deleted src/backend/common/utils/check_deployments.py as it is no longer needed. This script was used to check Azure AI Foundry model deployments and their statuses.
Introduces the main FastAPI router for agent framework v3, including endpoints for team management, plan creation, approval, agent messaging, and configuration upload. Adds callback handlers for agent responses and streaming, global debug access, and service skeletons for agents, base API, foundry, MCP, and team management. These files establish the backend structure for multi-agent orchestration and extensible service integration.
Introduces common lifecycle management for agents, new agent configuration models, and refactors ProxyAgent and ReasoningAgentTemplate to use agent_framework primitives. Removes Semantic Kernel dependencies, adds Azure AI Search integration, and streamlines agent creation and invocation logic for improved maintainability and extensibility.
Updated import paths from 'v3' to 'af' for consistency and modularity. Improved error handling, logging, and tool/resource collection logic in FoundryAgentTemplate. Cleaned up unused Bing references and clarified code interpreter and MCP tool handling. These changes enhance maintainability and agent lifecycle management.
Changed imports from 'agent_framework.azure' to 'agent_framework_azure_ai' for AzureAIAgentClient in foundry_agent.py and reasoning_agent.py. Also removed an unused import in lifecycle.py to clean up dependencies.
Migrates orchestration logic and related services from semantic-kernel (v3) to agent_framework, updating imports, manager classes, and workflow construction. Updates HumanApprovalMagenticManager and OrchestrationManager to use agent_framework APIs, adapts callback handling, and ensures compatibility with new message and agent structures. Cleans up legacy code and improves maintainability for future agent_framework-based enhancements.
fix: Macae rfp af 101725
Deleted the entire v3 API router, callbacks, and common service modules including agent, base API, foundry, and MCP services, as well as related configuration, models, and orchestration files. This change removes the v3 backend implementation, likely in preparation for a major refactor or migration.
Renamed src/backend/app_kernel.py to src/backend/app.py. Updated import paths to reference 'af' modules instead of 'v3' and 'messages_af' instead of 'messages_kernel' to reflect new module structure.
Updated Dockerfiles, app.py, and tests to reference 'app' instead of 'app_kernel'. This change standardizes the application entry point and module imports, improving consistency across the backend codebase.
Macae rfp af 101725
Replaced references to deprecated Semantic Kernel and v3 modules with agent_framework (af) equivalents throughout backend, database, and test files. Removed obsolete messages_kernel and utils_kernel files, updated import paths, and fixed minor typos. Updated documentation and README to reflect new entry points and usage.
Replaced Semantic Kernel dependencies and terminology with agent_framework equivalents across backend modules, including response handlers, configuration, agent factories, orchestration, and utility functions. Updated imports, class names, comments, and logic to reflect agent_framework usage. Adjusted test files and MCP authentication to use agent_framework constructs. This refactor enables the system to operate with agent_framework as the core agent orchestration and messaging library.
Macae rfp af 101725
Deleted src/mcp_server/auth.py, which contained MCP authentication and HostedMCPTool setup logic for the employee onboarding system. This change may indicate a refactor, deprecation, or migration of authentication and plugin management functionality.
Introduces extract_use_reasoning to ensure only explicit boolean True values set the use_reasoning flag, supporting both dict and attribute-style agent objects. Updates agent creation logic to use this stricter check.
Agent initialization now checks for existing database-backed AzureAIAgentClient instances and reuses them if available, improving persistence and resource management. The constructors for agent base classes were updated to accept and store model_deployment_name. FoundryAgentTemplate and ReasoningAgentTemplate now consistently use the database client if present, and only save new agents when necessary.
Updated RAI agent creation and compliance check functions to require explicit team configuration and memory store parameters. Refactored API endpoints to retrieve team and memory store before RAI checks, improving context handling and error reporting.
fix: changed the model name
Introduces a get_chat_client method to MCPEnabledBase for consistent agent client retrieval and updates agent initialization in FoundryAgentTemplate and ReasoningAgentTemplate to use it. Enhances error handling and validation in API router endpoints, including improved user and team configuration checks, and updates RAI validation calls to support additional parameters.
Updated `rai_validate_team_config` to accept additional parameters for improved validation. Refactored user authentication and error handling in API routes to ensure user and team existence before proceeding, and improved error reporting for missing or invalid user/team information.
fix: RFP added as a default team
Added checks for agent_id presence before returning or creating AzureAIAgentClient instances. Enhanced logging for client creation and error handling, and prevented saving database team agent when agent_id is None.
Deleted reasoning_agent.py and removed all references to ReasoningAgentTemplate in the agent factory and orchestration manager. The agent creation flow now exclusively uses FoundryAgentTemplate, and related comments and error messages have been updated accordingly. Also updated temperature setting in FoundryAgentTemplate to 1.0.
Macae rfp af 101725
Introduces a method to generate unique assistant IDs in MCPEnabledBase and adds get_agent_id to retrieve or create agent IDs. Updates FoundryAgentTemplate to assign agent IDs when initializing ChatAgent instances, ensuring consistent agent identification.
Macae rfp af 101725
Introduces a deployment_name field to agent team JSON files and TeamConfiguration model for dynamic model selection. Refactors agent ID generation and retrieval into utility functions, updates orchestration and lifecycle logic to use these utilities, and improves error logging and RAI validation handling in API routes.
Changed import statements in lifecycle.py and orchestration_manager.py to use the correct common module paths, improving consistency and resolving potential import errors.
Refactored generate_assistant_id and get_database_team_agent_id from utils_af.py to a new utils_agents.py for better separation of concerns. Updated imports in lifecycle.py and orchestration_manager.py to use the new module.
Updated rai_validate_team_config to initialize TeamConfiguration with default values and generated UUIDs. Also added deployment_name to TeamService creation from JSON data, ensuring the field is set even if missing.
…amework fixes for the id stuff - added temp difference btwn reasoning and non…
fix: added the RAI model variable and removed the other variable
…ent-framework RFP Branch: Add name to order data
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