refactor: Agent framework v2 changes

Author: Avijit-Microsoft

.github/workflows/deploy-KMGeneric.yml

@@ -118,7 +118,7 @@ jobs:
           echo "Generated SOLUTION_PREFIX: ${UNIQUE_SOLUTION_PREFIX}" 
       - name: Determine Tag Name Based on Branch
         id: determine_tag
-        run: echo "tagname=${{ github.ref_name == 'main' && 'latest_waf' || github.ref_name == 'dev' && 'dev' || github.ref_name == 'demo' && 'demo' || github.ref_name == 'dependabotchanges' && 'dependabotchanges' || 'latest_waf' }}" >> $GITHUB_OUTPUT
+        run: echo "tagname=${{ github.ref_name == 'main' && 'latest_afv2' || github.ref_name == 'dev' && 'dev' || github.ref_name == 'demo' && 'demo' || github.ref_name == 'dependabotchanges' && 'dependabotchanges' || 'latest_afv2' }}" >> $GITHUB_OUTPUT
       - name: Deploy Bicep Template
         id: deploy
         run: |

.github/workflows/docker-build.yml

@@ -61,7 +61,7 @@ jobs:
         id: determine_tag
         run: |
          if [[ "${{ github.ref_name }}" == "main" ]]; then
-          echo "tagname=latest_waf" >> $GITHUB_OUTPUT
+          echo "tagname=latest_afv2" >> $GITHUB_OUTPUT
          elif [[ "${{ github.ref_name }}" == "dev" ]]; then
           echo "tagname=dev" >> $GITHUB_OUTPUT
          elif [[ "${{ github.ref_name }}" == "demo" ]]; then

.github/workflows/job-azure-deploy.yml

@@ -456,8 +456,8 @@ jobs:
             echo "Current branch: $BRANCH_NAME"
             
             if [[ "$BRANCH_NAME" == "main" ]]; then
-              IMAGE_TAG="latest_waf"
-              echo "Using main branch - image tag: latest_waf"
+              IMAGE_TAG="latest_afv2"
+              echo "Using main branch - image tag: latest_afv2"
             elif [[ "$BRANCH_NAME" == "dev" ]]; then
               IMAGE_TAG="dev"
               echo "Using dev branch - image tag: dev"
@@ -471,8 +471,8 @@ jobs:
               IMAGE_TAG="dependabotchanges"
               echo "Using dependabotchanges branch - image tag: dependabotchanges"
             else
-              IMAGE_TAG="latest_waf"
-              echo "Using default for branch '$BRANCH_NAME' - image tag: latest_waf"
+              IMAGE_TAG="latest_afv2"
+              echo "Using default for branch '$BRANCH_NAME' - image tag: latest_afv2"
             fi
             
             echo "Using existing Docker image tag: $IMAGE_TAG"

.github/workflows/job-deploy-linux.yml

@@ -339,6 +339,39 @@ jobs:
           tenant-id: ${{ secrets.AZURE_TENANT_ID }}
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
 
+      - name: Run Create Agents Scripts
+        id: run_create_agents_scripts
+        continue-on-error: true
+        shell: bash
+        run: |
+          echo "Running run_create_agents_scripts.sh..."
+          bash ./infra/scripts/run_create_agents_scripts.sh
+          echo "✅ Create agents scripts completed successfully."
+
+      - name: Re-authenticate with Azure before retry (refresh OIDC token)
+        if: steps.run_create_agents_scripts.outcome == 'failure'
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+
+      - name: Retry Run Create Agents Scripts
+        if: steps.run_create_agents_scripts.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "⚠️ First attempt failed. Retrying run_create_agents_scripts.sh..."
+          sleep 20
+          bash ./infra/scripts/run_create_agents_scripts.sh
+          echo "✅ Create agents scripts completed successfully on retry."
+
+      - name: Re-authenticate with Azure before processing sample data (refresh OIDC token)
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+
       - name: Process Sample Data
         id: process_sample_data
         continue-on-error: true
@@ -394,6 +427,7 @@ jobs:
             echo "- **Container Web App URL**: [${{ env.WEB_APP_URL }}](${{ env.WEB_APP_URL }})" >> $GITHUB_STEP_SUMMARY
             echo "- **Container API App URL**: [${{ env.API_APP_URL }}](${{ env.API_APP_URL }})" >> $GITHUB_STEP_SUMMARY
             echo "- Successfully deployed to Azure with all resources configured" >> $GITHUB_STEP_SUMMARY
+            echo "- Agents created and configured successfully" >> $GITHUB_STEP_SUMMARY
             echo "- Schemas registered and sample data uploaded successfully" >> $GITHUB_STEP_SUMMARY
           else
             echo "### ❌ Deployment Failed" >> $GITHUB_STEP_SUMMARY

.github/workflows/job-deploy-windows.yml

@@ -364,6 +364,43 @@ jobs:
           tenant-id: ${{ secrets.AZURE_TENANT_ID }}
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
 
+      - name: Run Create Agents Scripts
+        id: run_create_agents_scripts
+        continue-on-error: true
+        shell: bash
+        env:
+          PYTHONIOENCODING: utf-8
+        run: |
+          echo "Running run_create_agents_scripts.sh..."
+          bash ./infra/scripts/run_create_agents_scripts.sh
+          echo "✅ Create agents scripts completed successfully."
+
+      - name: Re-authenticate with Azure before retry (refresh OIDC token)
+        if: steps.run_create_agents_scripts.outcome == 'failure'
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+
+      - name: Retry Run Create Agents Scripts
+        if: steps.run_create_agents_scripts.outcome == 'failure'
+        shell: bash
+        env:
+          PYTHONIOENCODING: utf-8
+        run: |
+          echo "⚠️ First attempt failed. Retrying run_create_agents_scripts.sh..."
+          sleep 20
+          bash ./infra/scripts/run_create_agents_scripts.sh
+          echo "✅ Create agents scripts completed successfully on retry."
+
+      - name: Re-authenticate with Azure before processing sample data (refresh OIDC token)
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+
       - name: Process Sample Data
         id: process_sample_data
         continue-on-error: true
@@ -435,6 +472,7 @@ jobs:
             echo "- **Container Web App URL**: [${{ env.WEB_APP_URL }}](${{ env.WEB_APP_URL }})" >> $GITHUB_STEP_SUMMARY
             echo "- **Container API App URL**: [${{ env.API_APP_URL }}](${{ env.API_APP_URL }})" >> $GITHUB_STEP_SUMMARY
             echo "- Successfully deployed to Azure with all resources configured" >> $GITHUB_STEP_SUMMARY
+            echo "- Agents created and configured successfully" >> $GITHUB_STEP_SUMMARY
             echo "- Schemas registered and sample data uploaded successfully" >> $GITHUB_STEP_SUMMARY
           else
             echo "### ❌ Deployment Failed" >> $GITHUB_STEP_SUMMARY

README.md

@@ -22,7 +22,7 @@ Analysts working with large volumes of conversational data can use this solution
 Solution overview
 </h2>
 
-Leverages Azure Content Understanding, Foundry IQ, Azure OpenAI Service, Semantic Kernel, Azure SQL Database, and Cosmos DB to process large volumes of conversational data. Audio and text inputs are analyzed through event-driven pipelines to extract and vectorize key information, orchestrate intelligent responses, and power an interactive web front-end for exploring insights using natural language.
+Leverages Azure Content Understanding, Foundry IQ, Azure OpenAI Service, Azure AI Agent Framework, Azure SQL Database, and Cosmos DB to process large volumes of conversational data. Audio and text inputs are analyzed through event-driven pipelines to extract and vectorize key information, orchestrate intelligent responses, and power an interactive web front-end for exploring insights using natural language.
 
 ### Solution architecture
 |![image](./documents/Images/ReadMe/solution-architecture.png)|
@@ -101,14 +101,13 @@ _Note: This is not meant to outline all costs as selected SKUs, scaled use, cust
 | [Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry) | Used to orchestrate and build AI workflows that combine Azure AI services. | Free Tier | [Pricing](https://azure.microsoft.com/pricing/details/ai-studio/) |
 | [Foundry IQ](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search) | Powers vector-based semantic search for retrieving indexed conversation data. | Standard S1; costs scale with document count and replica/partition settings. | [Pricing](https://azure.microsoft.com/pricing/details/search/) |
 | [Azure Storage Account](https://learn.microsoft.com/en-us/azure/storage/common/storage-account-overview) | Stores transcripts, intermediate outputs, and application assets. | Standard LRS; usage-based cost by storage/operations. | [Pricing](https://azure.microsoft.com/pricing/details/storage/blobs/) |
-| [Azure Key Vault](https://learn.microsoft.com/en-us/azure/key-vault/general/overview) | Secures secrets, credentials, and keys used across the application. | Standard Tier; cost per operation (e.g., secret retrieval). | [Pricing](https://azure.microsoft.com/pricing/details/key-vault/) |
+
 | [Azure AI Services (OpenAI)](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/overview) | Enables language understanding, summarization, entity extraction, and chat capabilities using GPT models. | S0 Tier; pricing depends on token volume and model used (e.g., GPT-4o-mini). | [Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/) |
 | [Azure Container Apps](https://learn.microsoft.com/en-us/azure/container-apps/overview) | Hosts microservices and APIs powering the front-end and backend orchestration. | Consumption plan with 0.5 vCPU, 1GiB memory; includes a free usage tier. | [Pricing](https://azure.microsoft.com/pricing/details/container-apps/) |
 | [Azure Container Registry](https://learn.microsoft.com/en-us/azure/container-registry/container-registry-intro) | Stores and serves container images used by Azure Container Apps. | Basic Tier; fixed daily cost per registry. | [Pricing](https://azure.microsoft.com/pricing/details/container-registry/) |
 | [Azure Monitor / Log Analytics](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/log-analytics-overview) | Collects and analyzes telemetry and logs from services and containers. | Pay-as-you-go; charges based on data ingestion volume. | [Pricing](https://azure.microsoft.com/pricing/details/monitor/) |
 | [Azure SQL Database](https://learn.microsoft.com/en-us/azure/azure-sql/database/sql-database-paas-overview) | Stores structured data including insights, metadata, and indexed results. | General Purpose Tier; can be provisioned or serverless. Fixed cost if provisioned. | [Pricing](https://azure.microsoft.com/pricing/details/azure-sql-database/single/) |
 | [Azure Cosmos DB](https://learn.microsoft.com/en-us/azure/cosmos-db/introduction) | Used for fast, globally distributed NoSQL data storage for chat history and vector metadata. | Autoscale or provisioned throughput; fixed minimum cost if provisioned. | [Pricing](https://azure.microsoft.com/en-us/pricing/details/cosmos-db/autoscale-provisioned/) |
-| [Azure Functions](https://learn.microsoft.com/en-us/azure/azure-functions/functions-overview) | Executes lightweight, serverless backend logic and event-driven workflows. | Consumption Tier; billed per execution and duration. | [Pricing](https://azure.microsoft.com/en-us/pricing/details/functions/) |
 
 
 <br/>
@@ -173,9 +172,7 @@ Supporting documentation
 
 ### Security guidelines
 
-This solution uses [Azure Key Vault](https://learn.microsoft.com/en-us/azure/key-vault/general/overview) to securely store secrets, connection strings, and API keys required by application components.
-
-It also leverages [Managed Identity](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/overview) for secure access to Azure resources during local development and production deployment, eliminating the need for hard-coded credentials.
+This solution leverages [Managed Identity](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/overview) for secure access to Azure resources during local development and production deployment, eliminating the need for hard-coded credentials.
 
 To maintain strong security practices, it is recommended that GitHub repositories built on this solution enable [GitHub secret scanning](https://docs.github.com/code-security/secret-scanning/about-secret-scanning) to detect accidental secret exposure.
 

azure.yaml

@@ -18,7 +18,10 @@ hooks:
       run: |
         Write-Host "Web app URL: "
         Write-Host "$env:WEB_APP_URL" -ForegroundColor Cyan
-        Write-Host "`nCreate and activate a virtual environment if not already done, then run the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
+
+        Write-Host "`nCreate and activate a virtual environment if not already done, then run the following command in the bash terminal to create agents:"
+        Write-Host "bash ./infra/scripts/run_create_agents_scripts.sh" -ForegroundColor Cyan
+        Write-Host "`nRun the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
         Write-Host "bash ./infra/scripts/process_sample_data.sh" -ForegroundColor Cyan
       shell: pwsh
       continueOnError: false
@@ -27,8 +30,11 @@ hooks:
       run: |
         echo "Web app URL: "
         echo $WEB_APP_URL
+
+        echo "\nCreate and activate a virtual environment if not already done, then run the following command in the bash terminal to create agents:"
+        echo "bash ./infra/scripts/run_create_agents_scripts.sh"
         echo ""
-        echo "Create and activate a virtual environment if not already done, then run the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
+        echo "\nRun the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
         echo "bash ./infra/scripts/process_sample_data.sh"
       shell: sh
       continueOnError: false

azure_custom.yaml

@@ -25,18 +25,27 @@ services:
 hooks:
   postprovision:
     windows:
+      run: |
+        Write-Host "Web app URL: "
+        Write-Host "$env:WEB_APP_URL" -ForegroundColor Cyan
+
+        Write-Host "`nCreate and activate a virtual environment if not already done, then run the following command in the bash terminal to create agents:"
+        Write-Host "bash ./infra/scripts/run_create_agents_scripts.sh" -ForegroundColor Cyan
+        Write-Host "`nRun the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
+        Write-Host "bash ./infra/scripts/process_sample_data.sh" -ForegroundColor Cyan
       shell: pwsh
       continueOnError: false
       interactive: true
-      run: |
-        Write-Host "Web app URL: $env:WEB_APP_URL" -ForegroundColor Cyan
-        Write-Host "`nRun the following command in bash, if sample data needs to be processed:`nbash ./infra/scripts/process_sample_data.sh" -ForegroundColor Yellow
     posix:
-      shell: sh
-      continueOnError: false
-      interactive: true
       run: |
-        echo "Web app URL: $WEB_APP_URL"
+        echo "Web app URL: "
+        echo $WEB_APP_URL
+
+        echo "\nCreate and activate a virtual environment if not already done, then run the following command in the bash terminal to create agents:"
+        echo "bash ./infra/scripts/run_create_agents_scripts.sh"
         echo ""
-        echo "Run the following command in bash, if sample data needs to be processed:"
+        echo "\nRun the following command in your Bash terminal. It will grant the necessary permissions between resources and your user account, and also process and load the sample data into the application."
         echo "bash ./infra/scripts/process_sample_data.sh"
+      shell: sh
+      continueOnError: false
+      interactive: true

docs/workshop/docs/workshop/requirements.txt

@@ -2,7 +2,7 @@
 azure-identity==1.21.0
 azure-ai-evaluation==1.5.0
 # Additional utilities
-semantic-kernel[azure]==1.28.0
+semantic-kernel[azure]==1.40.0
 azure-ai-projects==1.0.0b8
 openai==1.74.0
 pyodbc==5.2.0