feat: Integrated application insights instrumentation key into the bicep file (microsoft#42)

* feat: Integrated application insights instrumentation key into bicep files

* added application insights instrumentation key into env and readme file

* updated json file

* upgraded json file

* Update docker-build-and-push.yml

* Update docker-build-and-push.yml

* Update docker-build-and-push.yml

* Update docker-build-and-push.yml

* Update docker-build-and-push.yml

* Update docker-build-and-push.yml

* pyLint issues fixed

* lint issues fixed

---------

Co-authored-by: Roopan-Microsoft <168007406+Roopan-Microsoft@users.noreply.github.com>
Co-authored-by: Roopan P M <v-roopanpm@microsoft.com>

Author: Prashant-Microsoft

.github/workflows/docker-build-and-push.yml

@@ -32,6 +32,7 @@ jobs:
         uses: docker/setup-buildx-action@v1
 
       - name: Log in to Azure Container Registry
+        if: ${{ inputs.push == true && (github.ref_name == 'main' || github.ref_name == 'dev' || github.ref_name == 'demo' || github.ref_name == 'hotfix') }}
         uses: azure/docker-login@v2
         with:
           login-server: ${{ secrets.ACR_LOGIN_SERVER }}
@@ -48,15 +49,27 @@ jobs:
             echo "TAG=demo" >> $GITHUB_ENV
           elif [[ "${{ github.ref }}" == "refs/heads/hotfix" ]]; then
             echo "TAG=hotfix" >> $GITHUB_ENV
+          else
+            echo "TAG=pullrequest-ignore" >> $GITHUB_ENV
           fi
-      - name: Build and push Docker images
+          
+      - name: Build and push Docker images optionally
         run: |
           cd src/backend
           docker build -t ${{ secrets.ACR_LOGIN_SERVER }}/macaebackend:${{ env.TAG }} -f Dockerfile . && \
-          docker push ${{ secrets.ACR_LOGIN_SERVER }}/macaebackend:${{ env.TAG }} && \
-          echo "Backend image built and pushed successfully."
+          if [[ "${{ env.TAG }}" == "latest" || "${{ env.TAG }}" == "dev" || "${{ env.TAG }}" == "demo" || "${{ env.TAG }}" == "hotfix"  ]]; then
+            docker push ${{ secrets.ACR_LOGIN_SERVER }}/macaebackend:${{ env.TAG }} && \
+            echo "Backend image built and pushed successfully."
+          else
+            echo "Skipping Docker push for backend with tag: ${{ env.TAG }}"
+          fi
           cd ../frontend
           docker build -t ${{ secrets.ACR_LOGIN_SERVER }}/macaefrontend:${{ env.TAG }} -f Dockerfile . && \
-          docker push ${{ secrets.ACR_LOGIN_SERVER }}/macaefrontend:${{ env.TAG }} && \
-          echo "Frontend image built and pushed successfully."
+          if [[ "${{ env.TAG }}" == "latest" || "${{ env.TAG }}" == "dev" || "${{ env.TAG }}" == "demo" || "${{ env.TAG }}" == "hotfix"  ]]; then
+            docker push ${{ secrets.ACR_LOGIN_SERVER }}/macaefrontend:${{ env.TAG }} && \
+            echo "Frontend image built and pushed successfully."
+          else
+            echo "Skipping Docker push for frontend with tag: ${{ env.TAG }}"
+          fi
+
           

README.md

@@ -177,6 +177,9 @@ To add your newly created backend image:
         name: 'FRONTEND_SITE_NAME'
         value: 'https://<website Name>.azurewebsites.net'
 
+        name: 'APPLICATIONINSIGHTS_INSTRUMENTATION_KEY'
+        value: <Application Insights Instrumentation Key>
+
 - Click 'Save' and deploy your new revision
 
 To add the new container to your website run the following:

deploy/macae-continer-oc.json

@@ -6,7 +6,7 @@
     "_generator": {
       "name": "bicep",
       "version": "0.32.4.45862",
-      "templateHash": "17567587246932458853"
+      "templateHash": "13282901028774763433"
     }
   },
   "parameters": {
@@ -366,13 +366,18 @@
                 {
                   "name": "FRONTEND_SITE_NAME",
                   "value": "[format('https://{0}.azurewebsites.net', format(variables('uniqueNameFormat'), 'frontend'))]"
+                },
+                {
+                  "name": "APPLICATIONINSIGHTS_INSTRUMENTATION_KEY",
+                  "value": "[reference('appInsights').ConnectionString]"
                 }
               ]
             }
           ]
         }
       },
       "dependsOn": [
+        "appInsights",
         "cosmos::autogenDb",
         "containerAppEnv",
         "cosmos",

deploy/macae-continer.bicep

@@ -279,6 +279,10 @@ resource containerApp 'Microsoft.App/containerApps@2024-03-01' = {
               name: 'FRONTEND_SITE_NAME'
               value: 'https://${format(uniqueNameFormat, 'frontend')}.azurewebsites.net'
             }
+            {
+              name: 'APPLICATIONINSIGHTS_INSTRUMENTATION_KEY'
+              value: appInsights.properties.ConnectionString
+            }
           ]
         }
       ]

src/backend/.env.sample

@@ -5,6 +5,7 @@ COSMOSDB_CONTAINER=memory
 AZURE_OPENAI_ENDPOINT=
 AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o
 AZURE_OPENAI_API_VERSION=2024-08-01-preview
+APPLICATIONINSIGHTS_INSTRUMENTATION_KEY=
 
 BACKEND_API_URL='http://localhost:8000'
 FRONTEND_SITE_NAME='http://127.0.0.1:3000'

src/backend/agents/agentutils.py

@@ -1,11 +1,13 @@
 import json
 
-from autogen_core.components.models import (AssistantMessage,
-                                            AzureOpenAIChatCompletionClient)
+from autogen_core.components.models import (
+    AssistantMessage,
+    AzureOpenAIChatCompletionClient,
+)
 from pydantic import BaseModel
 
 from context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import InputTask, PlanStatus, Step, StepStatus
+from models.messages import Step
 
 common_agent_system_message = "If you do not have the information for the arguments of the function you need to call, do not call the function. Instead, respond back to the user requesting further information. You must not hallucinate or invent any of the information used as arguments in the function. For example, if you need to call a function that requires a delivery address, you must not generate 123 Example St. You must skip calling functions and return a clarification message along the lines of: Sorry, I'm missing some information I need to help you with that. Could you please provide the delivery address so I can do that for you?"
 
@@ -27,7 +29,7 @@ class FSMStateAndTransition(BaseModel):
             identifiedTargetState: str
             identifiedTargetTransition: str
 
-        cosmos = CosmosBufferedChatCompletionContext(session_id or "",user_id)
+        cosmos = CosmosBufferedChatCompletionContext(session_id or "", user_id)
         combined_LLM_messages = [
             AssistantMessage(content=step.action, source="GroupChatManager")
         ]

src/backend/agents/base_agent.py

@@ -3,18 +3,27 @@
 
 from autogen_core.base import AgentId, MessageContext
 from autogen_core.components import RoutedAgent, message_handler
-from autogen_core.components.models import (AssistantMessage,
-                                            AzureOpenAIChatCompletionClient,
-                                            LLMMessage, SystemMessage,
-                                            UserMessage)
+from autogen_core.components.models import (
+    AssistantMessage,
+    AzureOpenAIChatCompletionClient,
+    LLMMessage,
+    SystemMessage,
+    UserMessage,
+)
 from autogen_core.components.tool_agent import tool_agent_caller_loop
 from autogen_core.components.tools import Tool
 
 from context.cosmos_memory import CosmosBufferedChatCompletionContext
-from models.messages import (ActionRequest, ActionResponse,
-                             AgentMessage, Step, StepStatus)
+from models.messages import (
+    ActionRequest,
+    ActionResponse,
+    AgentMessage,
+    Step,
+    StepStatus,
+)
 from azure.monitor.events.extension import track_event
 
+
 class BaseAgent(RoutedAgent):
     def __init__(
         self,
@@ -95,7 +104,7 @@ async def handle_action_request(
                     step_id=message.step_id,
                 )
             )
-            
+
             track_event(
                 "Base agent - Added into the cosmos",
                 {
@@ -107,7 +116,7 @@ async def handle_action_request(
                     "step_id": message.step_id,
                 },
             )
-            
+
         except Exception as e:
             logging.exception(f"Error during LLM call: {e}")
             track_event(
@@ -121,14 +130,14 @@ async def handle_action_request(
                     "step_id": message.step_id,
                 },
             )
-            
+
             return
         print(f"Task completed: {result}")
 
         step.status = StepStatus.completed
         step.agent_reply = result
         await self._model_context.update_step(step)
-        
+
         track_event(
             "Base agent - Updated step and updated into the cosmos",
             {

src/backend/agents/generic.py

@@ -8,6 +8,7 @@
 from agents.base_agent import BaseAgent
 from context.cosmos_memory import CosmosBufferedChatCompletionContext
 
+
 async def dummy_function() -> str:
     # This is a placeholder function, for a proper Azure AI Search RAG process.
 

src/backend/agents/group_chat_manager.py

@@ -12,21 +12,16 @@
 from context.cosmos_memory import CosmosBufferedChatCompletionContext
 from models.messages import (
     ActionRequest,
-    ActionResponse,
     AgentMessage,
-    ApprovalRequest,
     BAgentType,
     HumanFeedback,
     HumanFeedbackStatus,
     InputTask,
     Plan,
-    PlanStatus,
     Step,
     StepStatus,
 )
 
-from datetime import datetime
-from typing import List
 from azure.monitor.events.extension import track_event
 
 
@@ -291,12 +286,10 @@ async def _execute_step(self, session_id: str, step: Step):
             agent=step.agent,
         )
         logging.info(f"Sending ActionRequest to {step.agent.value}")
-              
+
         if step.agent != "":
             agent_name = step.agent.value
-            formatted_agent = re.sub(
-                r"([a-z])([A-Z])", r"\1 \2", agent_name
-            )
+            formatted_agent = re.sub(r"([a-z])([A-Z])", r"\1 \2", agent_name)
         else:
             raise ValueError(f"Check {step.agent} is missing")
 

src/backend/agents/human.py

@@ -2,15 +2,12 @@
 import logging
 
 from autogen_core.base import AgentId, MessageContext
-from autogen_core.components import (RoutedAgent, default_subscription,
-                                     message_handler)
+from autogen_core.components import RoutedAgent, default_subscription, message_handler
 
 from context.cosmos_memory import CosmosBufferedChatCompletionContext
 from models.messages import (
     ApprovalRequest,
     HumanFeedback,
-    HumanClarification,
-    HumanFeedbackStatus,
     StepStatus,
     AgentMessage,
     Step,
@@ -23,7 +20,7 @@ class HumanAgent(RoutedAgent):
     def __init__(
         self,
         memory: CosmosBufferedChatCompletionContext,
-        user_id:str,
+        user_id: str,
         group_chat_manager_id: AgentId,
     ) -> None:
         super().__init__("HumanAgent")
@@ -83,7 +80,7 @@ async def handle_step_feedback(
             )
         )
         logging.info(f"HumanAgent sent approval request for step: {step}")
-        
+
         track_event(
             f"Human Agent - Approval request sent for step {step} and added into the cosmos",
             {