Refactor config usage to use AppConfig instance

Replaced direct os.getenv calls with values from the AppConfig instance throughout backend modules. Updated environment variable loading and usage in agent models, agent factory, and orchestration manager for consistency and improved maintainability. Added new config options to .env.sample and AppConfig for MCP, Azure Search, and Bing integration.

Author: Fr4nc3

src/backend/.env.sample

@@ -21,5 +21,15 @@ AZURE_BING_CONNECTION_NAME=
 REASONING_MODEL_NAME=o3
 APP_ENV=dev
 MCP_SERVER_ENDPOINT=http://localhost:9000/mcp
+MCP_SERVER_NAME=MyMC
+MCP_SERVER_DESCRIPTION=My MCP Server
+TENANT_ID=
+CLIENT_ID=
 BACKEND_API_URL=http://localhost:8000
-FRONTEND_SITE_NAME=*
+FRONTEND_SITE_NAME=*
+SUPPORTED_MODELS=
+AZURE_AI_SEARCH_CONNECTION_NAME=
+AZURE_AI_SEARCH_INDEX_NAME=
+AZURE_AI_SEARCH_ENDPOINT=
+AZURE_AI_SEARCH_API_KEY=
+BING_CONNECTION_NAME=

src/backend/app_kernel.py

@@ -17,11 +17,10 @@
                                            InputTask, Plan, PlanStatus,
                                            PlanWithSteps, Step, UserLanguage)
 from common.utils.event_utils import track_event_if_configured
-from common.utils.utils_date import format_dates_in_messages
+
 # Updated import for KernelArguments
 from common.utils.utils_kernel import rai_success
-from common.utils.websocket_streaming import (websocket_streaming_endpoint,
-                                              ws_manager)
+
 # FastAPI imports
 from fastapi import (FastAPI, HTTPException, Query, Request, WebSocket,
                      WebSocketDisconnect)
@@ -30,7 +29,7 @@
 # Local imports
 from middleware.health_check import HealthCheckMiddleware
 from v3.api.router import app_v3
-from v3.config.settings import connection_config
+
 # Semantic Kernel imports
 from v3.orchestration.orchestration_manager import OrchestrationManager
 

src/backend/common/config/app_config.py

@@ -55,7 +55,7 @@ def __init__(self):
         self.AZURE_BING_CONNECTION_NAME = self._get_optional(
             "AZURE_BING_CONNECTION_NAME"
         )
-
+        self.SUPPORTED_MODELS = self._get_optional("SUPPORTED_MODELS")
         # Frontend settings
         self.FRONTEND_SITE_NAME = self._get_optional(
             "FRONTEND_SITE_NAME", "http://127.0.0.1:3000"
@@ -74,6 +74,15 @@ def __init__(self):
         # Optional MCP server endpoint (for local MCP server or remote)
         # Example: http://127.0.0.1:8000/mcp
         self.MCP_SERVER_ENDPOINT = self._get_optional("MCP_SERVER_ENDPOINT")
+        self.MCP_SERVER_NAME = self._get_optional("MCP_SERVER_NAME")
+        self.MCP_SERVER_DESCRIPTION = self._get_optional("MCP_SERVER_DESCRIPTION")
+        self.TENANT_ID = self._get_optional("TENANT_ID")
+        self.CLIENT_ID = self._get_optional("CLIENT_ID")
+        self.AZURE_AI_SEARCH_CONNECTION_NAME = self._get_optional("AZURE_AI_SEARCH_CONNECTION_NAME")
+        self.AZURE_AI_SEARCH_INDEX_NAME = self._get_optional("AZURE_AI_SEARCH_INDEX_NAME")
+        self.AZURE_AI_SEARCH_ENDPOINT = self._get_optional("AZURE_AI_SEARCH_ENDPOINT")
+        self.AZURE_AI_SEARCH_API_KEY = self._get_optional("AZURE_AI_SEARCH_API_KEY")
+        self.BING_CONNECTION_NAME = self._get_optional("BING_CONNECTION_NAME")  
 
         test_team_json = self._get_optional("TEST_TEAM_JSON")
 

src/backend/v3/api/router.py

@@ -7,7 +7,6 @@
 
 import v3.models.messages as messages
 from auth.auth_utils import get_authenticated_user_details
-from common.config.app_config import config
 from common.database.database_factory import DatabaseFactory
 from common.models.messages_kernel import (GeneratePlanRequest, InputTask,
                                            TeamSelectionRequest)

src/backend/v3/common/services/foundry_service.py

@@ -54,8 +54,7 @@ async def list_model_deployments(self) -> List[Dict[str, Any]]:
 
         try:
             # Get Azure Management API token (not Cognitive Services token)
-            credential = config.get_azure_credentials()
-            token = credential.get_token(config.AZURE_MANAGEMENT_SCOPE)
+            token = config.get_access_token()
 
             # Extract Azure OpenAI resource name from endpoint URL
             openai_endpoint = config.AZURE_OPENAI_ENDPOINT

src/backend/v3/magentic_agents/magentic_agent_factory.py

@@ -15,7 +15,7 @@
                                                     SearchConfig)
 from v3.magentic_agents.proxy_agent import ProxyAgent
 from v3.magentic_agents.reasoning_agent import ReasoningAgentTemplate
-
+from common.config.app_config import config
 
 class UnsupportedModelError(Exception):
     """Raised when an unsupported model is specified."""
@@ -65,7 +65,7 @@ async def create_agent_from_config(self, agent_obj: SimpleNamespace) -> Union[Fo
             return ProxyAgent(user_id=user_id)
 
         # Validate supported models
-        supported_models = json.loads(os.getenv("SUPPORTED_MODELS"))
+        supported_models = json.loads(config.SUPPORTED_MODELS)
 
         if deployment_name not in supported_models:
             raise UnsupportedModelError(f"Model '{deployment_name}' not supported. Supported: {supported_models}")
@@ -95,7 +95,7 @@ async def create_agent_from_config(self, agent_obj: SimpleNamespace) -> Union[Fo
         # Create appropriate agent
         if use_reasoning:
             # Get reasoning specific configuration
-            azure_openai_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+            azure_openai_endpoint = config.AZURE_OPENAI_ENDPOINT
 
             agent = ReasoningAgentTemplate(
                 agent_name=agent_obj.name,

src/backend/v3/magentic_agents/models/agent_models.py

@@ -2,7 +2,7 @@
 
 import os
 from dataclasses import dataclass
-
+from common.config.app_config import config
 
 @dataclass(slots=True)
 class MCPConfig:
@@ -15,12 +15,12 @@ class MCPConfig:
 
     @classmethod
     def from_env(cls) -> "MCPConfig":
-        url = os.getenv("MCP_SERVER_ENDPOINT")
-        name = os.getenv("MCP_SERVER_NAME")
-        description = os.getenv("MCP_SERVER_DESCRIPTION")
-        tenant_id = os.getenv("TENANT_ID")
-        client_id = os.getenv("CLIENT_ID")
-        
+        url = config.MCP_SERVER_ENDPOINT
+        name = config.MCP_SERVER_NAME
+        description = config.MCP_SERVER_DESCRIPTION
+        tenant_id = config.TENANT_ID
+        client_id = config.CLIENT_ID
+
         # Raise exception if any required environment variable is missing
         if not all([url, name, description, tenant_id, client_id]):
             raise ValueError(f"{cls.__name__} Missing required environment variables")
@@ -40,7 +40,7 @@ class BingConfig:
 
     @classmethod
     def from_env(cls) -> "BingConfig":
-        connection_name = os.getenv("BING_CONNECTION_NAME")
+        connection_name = config.BING_CONNECTION_NAME
 
         # Raise exception if required environment variable is missing
         if not connection_name:
@@ -60,11 +60,11 @@ class SearchConfig:
 
     @classmethod
     def from_env(cls) -> "SearchConfig":
-        connection_name = os.getenv("AZURE_AI_SEARCH_CONNECTION_NAME")
-        index_name = os.getenv("AZURE_AI_SEARCH_INDEX_NAME")
-        endpoint = os.getenv("AZURE_AI_SEARCH_ENDPOINT")
-        api_key = os.getenv("AZURE_AI_SEARCH_API_KEY")
-        
+        connection_name = config.AZURE_AI_SEARCH_CONNECTION_NAME
+        index_name = config.AZURE_AI_SEARCH_INDEX_NAME
+        endpoint = config.AZURE_AI_SEARCH_ENDPOINT
+        api_key = config.AZURE_AI_SEARCH_API_KEY
+
         # Raise exception if any required environment variable is missing
         if not all([connection_name, index_name, endpoint]):
             raise ValueError(f"{cls.__name__} Missing required Azure Search environment variables")

src/backend/v3/magentic_agents/reasoning_agent.py

@@ -9,7 +9,7 @@
 from v3.magentic_agents.common.lifecycle import MCPEnabledBase
 from v3.magentic_agents.models.agent_models import MCPConfig, SearchConfig
 from v3.magentic_agents.reasoning_search import ReasoningSearch
-
+from common.config.app_config import config
 
 class ReasoningAgentTemplate(MCPEnabledBase):
     """
@@ -47,7 +47,7 @@ def ad_token_provider() -> str:
         chat = AzureChatCompletion(
             deployment_name=self._model_deployment_name,
             endpoint=self._openai_endpoint,
-            ad_token_provider=ad_token_provider
+            ad_token_provider=config.get_access_token()
         )
         self.kernel.add_service(chat)
 

src/backend/v3/orchestration/orchestration_manager.py

@@ -20,6 +20,7 @@
                                             streaming_agent_response_callback)
 from v3.config.settings import (config, connection_config, current_user_id,
                                 orchestration_config)
+from common.config.app_config import config
 from v3.magentic_agents.magentic_agent_factory import MagenticAgentFactory
 from v3.orchestration.human_approval_manager import \
     HumanApprovalMagenticManager
@@ -43,21 +44,15 @@ async def init_orchestration(cls, agents: List, user_id: str = None)-> MagenticO
             temperature=0.1
         )
 
-        # Create a token provider function for Azure OpenAI
-        credential = SyncDefaultAzureCredential()
-
-        def get_token():
-            token = credential.get_token("https://cognitiveservices.azure.com/.default")
-            return token.token
 
         # 1. Create a Magentic orchestration with Azure OpenAI
         magentic_orchestration = MagenticOrchestration(
             members=agents,
             manager=HumanApprovalMagenticManager(
                 chat_completion_service=AzureChatCompletion(
-                    deployment_name=os.getenv("AZURE_OPENAI_MODEL_NAME"),
-                    endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
-                    ad_token_provider=get_token  # Use token provider function
+                    deployment_name=config.AZURE_OPENAI_DEPLOYMENT_NAME,
+                    endpoint=config.AZURE_OPENAI_ENDPOINT,
+                    ad_token_provider=config.get_access_token()
                 ),
                 execution_settings=execution_settings
             ),