Update Application Insights configuration and refactor response format handling in agent classes

Author: Abdul-Microsoft

src/backend/.env.sample

@@ -14,7 +14,7 @@ AZURE_AI_RESOURCE_GROUP=
 AZURE_AI_PROJECT_NAME=
 AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
 AZURE_AI_AGENT_MODEL_DEPLOYMENT_NAME=gpt-4o
-#APPLICATIONINSIGHTS_CONNECTION_STRING=
+APPLICATIONINSIGHTS_CONNECTION_STRING=
 AZURE_AI_AGENT_ENDPOINT=
 
 BACKEND_API_URL=http://localhost:8000

src/backend/app_kernel.py

@@ -1,6 +1,7 @@
 # app_kernel.py
 import asyncio
 import logging
+import os
 import uuid
 from typing import Dict, List, Optional
 
@@ -9,7 +10,7 @@
 from auth.auth_utils import get_authenticated_user_details
 
 # Azure monitoring
-# from azure.monitor.opentelemetry import configure_azure_monitor
+from azure.monitor.opentelemetry import configure_azure_monitor
 from config_kernel import Config
 from event_utils import track_event_if_configured
 
@@ -33,19 +34,19 @@
 # Updated import for KernelArguments
 from utils_kernel import initialize_runtime_and_context, rai_success
 
-# Check if the Application Insights Instrumentation Key is set in the environment variables
-# connection_string = os.getenv("APPLICATIONINSIGHTS_CONNECTION_STRING")
-# if connection_string:
-#     # Configure Application Insights if the Instrumentation Key is found
-#     configure_azure_monitor(connection_string=connection_string)
-#     logging.info(
-#         "Application Insights configured with the provided Instrumentation Key"
-#     )
-# else:
-#     # Log a warning if the Instrumentation Key is not found
-#     logging.warning(
-#         "No Application Insights Instrumentation Key found. Skipping configuration"
-#     )
+#Check if the Application Insights Instrumentation Key is set in the environment variables
+connection_string = os.getenv("APPLICATIONINSIGHTS_CONNECTION_STRING")
+if connection_string:
+    # Configure Application Insights if the Instrumentation Key is found
+    configure_azure_monitor(connection_string=connection_string)
+    logging.info(
+        "Application Insights configured with the provided Instrumentation Key"
+    )
+else:
+    # Log a warning if the Instrumentation Key is not found
+    logging.warning(
+        "No Application Insights Instrumentation Key found. Skipping configuration"
+    )
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)

src/backend/kernel_agents/agent_factory.py

@@ -6,7 +6,8 @@
 
 # Import the new AppConfig instance
 from app_config import config
-
+from azure.ai.agents.models import (ResponseFormatJsonSchema,
+                                      ResponseFormatJsonSchemaType)
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from kernel_agents.agent_base import BaseAgent
 from kernel_agents.generic_agent import GenericAgent
@@ -264,14 +265,13 @@ async def create_all_agents(
             temperature=temperature,
             agent_instances=agent_instances,  # Pass agent instances to the planner
             client=client,
-            response_format={
-                "type": "json_schema",
-                "json_schema": {
-                    "name": PlannerResponsePlan.__name__,
-                    "description": f"respond with {PlannerResponsePlan.__name__.lower()}",
-                    "schema": PlannerResponsePlan.model_json_schema()
-                }
-            },
+            response_format=ResponseFormatJsonSchemaType(
+                json_schema=ResponseFormatJsonSchema(
+                    name=PlannerResponsePlan.__name__,
+                    description=f"respond with {PlannerResponsePlan.__name__.lower()}",
+                    schema=PlannerResponsePlan.model_json_schema(),
+                )
+            ),
         )
         agent_instances[AgentType.PLANNER.value] = (
             planner_agent  # to pass it to group chat manager
@@ -326,4 +326,4 @@ def clear_cache(cls, session_id: Optional[str] = None) -> None:
         else:
             cls._agent_cache.clear()
             cls._azure_ai_agent_cache.clear()
-            logger.info("Cleared all agent caches")
+            logger.info("Cleared all agent caches")

src/backend/kernel_agents/planner_agent.py

@@ -3,6 +3,8 @@
 import uuid
 from typing import Any, Dict, List, Optional, Tuple
 
+from azure.ai.agents.models import (ResponseFormatJsonSchema,
+                                      ResponseFormatJsonSchemaType)
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from event_utils import track_event_if_configured
 from kernel_agents.agent_base import BaseAgent
@@ -131,40 +133,36 @@ async def create(
         try:
             logging.info("Initializing PlannerAgent from async init azure AI Agent")
 
-            # Construct response_format with the required 'type' field
-            response_format = {
-                "type": "json_schema",  # Add the missing type field
-                "json_schema": {
-                    "name": PlannerResponsePlan.__name__,
-                    "description": f"respond with {PlannerResponsePlan.__name__.lower()}",
-                    "schema": PlannerResponsePlan.model_json_schema()
-                }
-            }
-
             # Create the Azure AI Agent using AppConfig with string instructions
             agent_definition = await cls._create_azure_ai_agent_definition(
                 agent_name=agent_name,
-                instructions=cls._get_template(),  # Pass the formatted string
+                instructions=cls._get_template(),  # Pass the formatted string, not an object
                 temperature=0.0,
-                response_format=response_format,
+                response_format=ResponseFormatJsonSchemaType(
+                    json_schema=ResponseFormatJsonSchema(
+                        name=PlannerResponsePlan.__name__,
+                        description=f"respond with {PlannerResponsePlan.__name__.lower()}",
+                        schema=PlannerResponsePlan.model_json_schema(),
+                    )
+                ),
             )
 
-        except Exception as exc:
-            logging.error("Error initializing PlannerAgent definition: %s", exc)
-            raise
+            return cls(
+                session_id=session_id,
+                user_id=user_id,
+                memory_store=memory_store,
+                tools=tools,
+                system_message=system_message,
+                agent_name=agent_name,
+                available_agents=available_agents,
+                agent_instances=agent_instances,
+                client=client,
+                definition=agent_definition,
+            )
 
-        return cls(
-            session_id=session_id,
-            user_id=user_id,
-            memory_store=memory_store,
-            tools=tools,
-            system_message=system_message,
-            agent_name=agent_name,
-            available_agents=available_agents,
-            agent_instances=agent_instances,
-            client=client,
-            definition=agent_definition,
-        )
+        except Exception as e:
+            logging.error(f"Failed to create Azure AI Agent for PlannerAgent: {e}")
+            raise
 
     async def handle_input_task(self, input_task: InputTask) -> str:
         """Handle the initial input task from the user.
@@ -598,4 +596,4 @@ def _get_template():
             Choose from {{$agents_str}} ONLY for planning your steps.
 
             """
-        return instruction_template
+        return instruction_template