refactor: Code clean up, EXP changes

.github/dependabot.yml

@@ -15,7 +15,7 @@ updates:
         patterns:
           - "*"
 
-  # 2. Python dependencies – App
+  # 2. Python dependencies – App
   - package-ecosystem: "pip"
     directory: "/src/App"
     schedule:
@@ -28,22 +28,8 @@ updates:
       backend-deps:
         patterns:
           - "*"
-
-  # 3. Python dependencies – Azure Function
-  - package-ecosystem: "pip"
-    directory: "/src/AzureFunction"
-    schedule:
-      interval: "monthly"
-    commit-message:
-      prefix: "build"
-    target-branch: "dependabotchanges"
-    open-pull-requests-limit: 10
-    groups:
-      backend-deps:
-        patterns:
-          - "*"
-
-  # 4. Python dependencies – Fabric Scripts
+
+  # 3. Python dependencies – Fabric Scripts
   - package-ecosystem: "pip"
     directory: "/src/infra/scripts/fabric_scripts"
     schedule:
@@ -57,7 +43,7 @@ updates:
         patterns:
           - "*"
 
-  # 5. Python dependencies – Index Scripts
+  # 4. Python dependencies – Index Scripts
   - package-ecosystem: "pip"
     directory: "/src/infra/scripts/index_scripts"
     schedule:

.github/workflows/test_automation.yml

@@ -0,0 +1,111 @@
+name: Test Automation ClientAdvisor
+
+on:
+  push:
+    branches:
+      - main
+      - dev
+
+    paths:
+      - 'tests/e2e-test/**'
+  schedule:
+      - cron: '0 13 * * *'  # Runs at 1 PM UTC 
+  workflow_dispatch:
+
+env:
+    url: ${{ vars.CLIENT_ADVISOR_URL }}
+    accelerator_name: "Client Advisor"
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.13'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r tests/e2e-test/requirements.txt
+
+      - name: Ensure browsers are installed
+        run: python -m playwright install --with-deps chromium
+
+      - name: Run tests(1)
+        id: test1
+        run: |
+          xvfb-run pytest --headed --html=report/report.html --self-contained-html
+        working-directory: tests/e2e-test
+        continue-on-error: true
+
+      - name: Sleep for 30 seconds
+        if: ${{ steps.test1.outcome == 'failure' }}
+        run: sleep 30s
+        shell: bash
+
+      - name: Run tests(2)
+        if: ${{ steps.test1.outcome == 'failure' }}
+        id: test2
+        run: |
+          xvfb-run pytest --headed --html=report/report.html --self-contained-html
+        working-directory: tests/e2e-test
+        continue-on-error: true
+
+      - name: Sleep for 60 seconds
+        if: ${{ steps.test2.outcome == 'failure' }}
+        run: sleep 60s
+        shell: bash
+
+      - name: Run tests(3)
+        if: ${{ steps.test2.outcome == 'failure' }}
+        id: test3
+        run: |
+          xvfb-run pytest --headed --html=report/report.html --self-contained-html
+        working-directory: tests/e2e-test
+
+      - name: Upload test report
+        id: upload_report
+        uses: actions/upload-artifact@v4
+        if: ${{ !cancelled() }}
+        with:
+          name: test-report
+          path: tests/e2e-test/report/*
+
+      - name: Send Notification
+        if: always()
+        run: |
+          RUN_URL="https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"
+          REPORT_URL=${{ steps.upload_report.outputs.artifact-url }}
+          IS_SUCCESS=${{ steps.test1.outcome == 'success' || steps.test2.outcome == 'success' || steps.test3.outcome == 'success' }}
+          # Construct the email body
+          if [ "$IS_SUCCESS" = "true" ]; then
+            EMAIL_BODY=$(cat <<EOF
+            {
+              "body": "<p>Dear Team,</p><p>We would like to inform you that the ${{ env.accelerator_name }} Test Automation process has completed successfully.</p><p><strong>Run URL:</strong> <a href=\"${RUN_URL}\">${RUN_URL}</a>
+              </p><p><strong>Test Report:</strong> <a href=\"${REPORT_URL}\">${REPORT_URL}</a></p><p>Best regards,
+              Your Automation Team</p>",
+              "subject": "${{ env.accelerator_name }} Test Automation - Success"
+            }
+          EOF
+            )
+          else
+            EMAIL_BODY=$(cat <<EOF
+            {
+              "body": "<p>Dear Team,</p><p>We would like to inform you that the ${{ env.accelerator_name }} Test Automation process  has encountered an issue and has failed to complete successfully.</p><p><strong>Run URL:</strong> <a href=\"${RUN_URL}\">${RUN_URL}</a>
+               ${OUTPUT}</p><p><strong>Test Report:</strong> <a href=\"${REPORT_URL}\">${REPORT_URL}</a></p><p>Please investigate the matter at your earliest convenience.</p><p>Best regards,
+                Your Automation Team</p>",
+              "subject": "${{ env.accelerator_name }} Test Automation - Failure"
+            }
+          EOF
+            )
+          fi
+
+          # Send the notification
+          curl -X POST "${{ secrets.EMAILNOTIFICATION_LOGICAPP_URL_TA}}" \
+            -H "Content-Type: application/json" \
+            -d "$EMAIL_BODY" || echo "Failed to send notification"

docs/CustomizingAzdParameters.md

@@ -3,41 +3,35 @@
 By default this template will use the environment name as the prefix to prevent naming collisions within Azure. The parameters below show the default values. You only need to run the statements below if you need to change the values. 
 
 
-> To override any of the parameters, run `azd env set <key> <value>` before running `azd up`. On the first azd command, it will prompt you for the environment name. Be sure to choose 3-20 characters alphanumeric unique name. 
+> To override any of the parameters, run `azd env set <PARAMETER_NAME> <VALUE>` before running `azd up`. On the first azd command, it will prompt you for the environment name. Be sure to choose 3-20 charaters alphanumeric unique name. 
+
+## Parameters
+
+| Name                          | Type    | Default Value       | Purpose                                                                                              |
+| -----------------------------| ------- | ------------------- | ---------------------------------------------------------------------------------------------------- |
+| `AZURE_ENV_NAME`            | string  | `azdtemp`           | Used as a prefix for all resource names to ensure uniqueness across environments.                    |
+| `AZURE_ENV_COSMOS_LOCATION`             | string  | `eastus2`    | Location of the Cosmos DB instance. Choose from (allowed values: `swedencentral`, `australiaeast`).      |
+| `AZURE_ENV_MODEL_DEPLOYMENT_TYPE`             | string  | `GlobalStandard`    | Change the Model Deployment Type (allowed values: Standard, GlobalStandard).                         |
+| `AZURE_ENV_MODEL_NAME`               | string  | `gpt-4o-mini`            | Set the GPT model name (allowed values: `gpt-4o`).                                                      |
+| `AZURE_ENV_MODEL_VERSION`     | string  | `2025-01-01-preview`        | Set the Azure OpenAI API version (allowed values: 2024-08-06).                                       |
+| `AZURE_ENV_MODEL_CAPACITY`     | integer | `30`               | Set the model capacity for GPT deployment. Choose based on your Azure quota and usage needs.         |
+| `AZURE_ENV_EMBEDDING_MODEL_NAME`            | string  | `text-embedding-ada-002`  | Set the model name used for embeddings.                                                              |
+| `AZURE_ENV_EMBEDDING_MODEL_CAPACITY` | integer | `80`              | Set the capacity for embedding model deployment.                                                     |
+| `AZURE_ENV_IMAGETAG`                  | string  | `latest`            | Set the image tag (allowed values: `latest`, `dev`, `hotfix`).                                             |
+| `AZURE_ENV_OPENAI_LOCATION`       | string  | `eastus2`    | Location of the Azure OpenAI resource. Choose from (allowed values: `swedencentral`, `australiaeast`).   |
+| `AZURE_LOCATION`            | string  | `japaneast`         | Sets the Azure region for resource deployment.  |
+| `AZURE_ENV_LOG_ANALYTICS_WORKSPACE_ID`            | string  | `<Existing Workspace Id>`         | Reuses an existing Log Analytics Workspace instead of provisioning a new one.   |
+
+## How to Set a Parameter
+To customize any of the above values, run the following command **before** `azd up`:
+
+```bash
+azd env set <PARAMETER_NAME> <VALUE>
 
-
-Change the Secondary Location (example: eastus2, westus2, etc.)
-
-```shell
-azd env set AZURE_ENV_SECONDARY_LOCATION eastus2
-```
-
-Change the Model Deployment Type (allowed values: Standard, GlobalStandard)
-
-```shell
-azd env set AZURE_ENV_MODEL_DEPLOYMENT_TYPE Standard
-```
-
-Set the Model Name (allowed values: gpt-4, gpt-4o)
-
-```shell
-azd env set AZURE_ENV_MODEL_NAME gpt-4o
-```
-
-Change the Model Capacity (choose a number based on available GPT model capacity in your subscription)
-
-```shell
-azd env set AZURE_ENV_MODEL_CAPACITY 30
-```
-
-Change the Embedding Model 
-
-```shell
-azd env set AZURE_ENV_EMBEDDING_MODEL_NAME text-embedding-ada-002
 ```
 
-Change the Embedding Deployment Capacity (choose a number based on available embedding model capacity in your subscription)
+**Example:**
 
-```shell
-azd env set AZURE_ENV_EMBEDDING_MODEL_CAPACITY 80
+```bash
+azd env set AZURE_LOCATION westus2
 ```

docs/DeploymentGuide.md

@@ -104,16 +104,24 @@ Consider the following settings during your deployment to modify specific settin
 
 When you start the deployment, most parameters will have **default values**, but you can update the below settings by following the steps  [here](CustomizingAzdParameters.md):  
 
-| **Setting** | **Description** |  **Default value** |
-|------------|----------------|  ------------|
-| **Azure OpenAI Location** | The region where OpenAI deploys | eastus2 | 
-| **Environment Name** | A **3-20 character alphanumeric value** used to generate a unique ID to prefix the resources. |  byocatemplate |
-| **Cosmos Location** | A **less busy** region for **CosmosDB**, useful in case of availability constraints. |  eastus2 |
-| **Deployment Type** | Select from a drop-down list. |  Global Standard |
-| **GPT Model** | OpenAI GPT model  | gpt-4o-mini |  
-| **GPT Model Deployment Capacity** | Configure capacity for **GPT models**. | 30k |
-| **Embedding Model** | OpenAI embedding model |  text-embedding-ada-002 |
-| **Embedding Model Capacity** | Set the capacity for **embedding models**. |  80k |
+
+| **Setting**                          | **Description**                                                                                    | **Default value**        |
+| ------------------------------------ | -------------------------------------------------------------------------------------------------- | ------------------------ |
+| **Azure OpenAI Location**            | The region where Azure OpenAI deploys. Choose from `swedencentral`, `australiaeast`, etc.        | `eastus2`                |
+| **Environment Name**                 | A **3-20 character alphanumeric value** used to generate a unique ID to prefix the resources.      | `azdtemp`                |
+| **Cosmos Location**                  | A **less busy** region for **CosmosDB**, useful in case of availability constraints.               | `eastus2`                |
+| **Deployment Type**                  | Select from a drop-down list (`Standard`, `GlobalStandard`).                                       | `GlobalStandard`         |
+| **GPT Model**                        | Azure OpenAI GPT model to deploy.                                                                  | `gpt-4o-mini`            |
+| **GPT Model Deployment Capacity**    | Configure capacity for **GPT models**. Choose based on Azure OpenAI quota.                         | `30`                     |
+| **Embedding Model**                  | OpenAI embedding model used for vector similarity.                                                 | `text-embedding-ada-002` |
+| **Embedding Model Capacity**         | Set the capacity for **embedding models**. Choose based on usage and quota.                        | `80`                     |
+| **Image Tag**                        | The version of the Docker image to use (e.g., `latest`, `dev`, `hotfix`).                          | `latest`                 |
+| **Azure OpenAI API Version**         | Set the API version for OpenAI model deployments.                                                  | `2025-01-01-preview`     |
+| **AZURE\_LOCATION**                  | Sets the Azure region for resource deployment. | `japaneast`              |
+| **Existing Log Analytics Workspace** | To reuse an existing Log Analytics Workspace ID instead of creating a new one.                     | *(empty)*                |
+
+
+
 
 </details>
 

docs/FabricDeployment.md

@@ -1,5 +1,8 @@
 ## Fabric Deployment
-## Step 1: Create Fabric workspace
+## Step 1: Create or Use an Existing Microsoft Fabric Workspace
+
+ℹ️ Note: If you already have an existing Microsoft Fabric Workspace, you can **skip this step** and proceed to Step 2. To retrieve an existing Workspace ID, check **Point 5 below**.
+
 1.  Navigate to ([Fabric Workspace](https://app.fabric.microsoft.com/))
 2.  Click on Workspaces from left Navigation
 3.  Click on + New Workspace
@@ -19,7 +22,7 @@
       - ```cd ./Build-your-own-copilot-Solution-Accelerator/infra/scripts/fabric_scripts```
       - ```sh ./run_fabric_items_scripts.sh keyvault_param workspaceid_param solutionprefix_param```  
          1. keyvault_param - the name of the keyvault that was created in Step 1
-         2. workspaceid_param - the workspaceid created in Step 2
+         2. workspaceid_param - Existing Workspaceid or workspaceid created in Step 2
          3. solutionprefix_param - prefix used to append to lakehouse upon creation
 4.  Get Fabric Lakehouse connection details:
 5.  Once deployment is complete, navigate to Fabric Workspace

docs/LocalSetupAndDeploy.md

@@ -40,9 +40,11 @@ Follow these steps to deploy the application to Azure App Service:
 If this is your first time deploying the app, use the `az webapp up` command. Run the following commands from the `App` folder, replacing the placeholders with your desired values:
 
 ```sh
-az webapp up --runtime PYTHON:3.11 --sku B1 --name <new-app-name> --resource-group <resource-group-name> --location <azure-region> --subscription <subscription-name>
+az webapp up --runtime PYTHON:3.11 --sku B1 --name <new-app-name> --resource-group <resource-group-name> --location <azure-region> --subscription <subscription-id>
 
-az webapp config set --startup-file "python3 -m gunicorn app:app" --name <new-app-name>  --resource-group <resource-group-name>
+az webapp config set --startup-file "python3 -m uvicorn app:app --host 0.0.0.0 --port 8000" --name <new-app-name>  --resource-group <resource-group-name>
+
+az webapp config appsettings set --resource-group <resource-group-name> --name <new-app-name> --settings WEBSITES_PORT=8000
 ```
 
 Next, configure the required environment variables in the deployed app to ensure it functions correctly.
@@ -83,7 +85,7 @@ az webapp up \
   --resource-group <resource-group-name>
 
 az webapp config set \
-  --startup-file "python3 -m gunicorn app:app" \
+  --startup-file "python3 -m uvicorn app:app --host 0.0.0.0 --port 8000" \
   --name <existing-app-name> --resource-group <resource-group-name>
 ```
 

infra/deploy_ai_foundry.bicep

@@ -9,6 +9,7 @@ param gptDeploymentCapacity int
 param embeddingModel string
 param embeddingDeploymentCapacity int
 param managedIdentityObjectId string
+param existingLogAnalyticsWorkspaceId string = ''
 
 // Load the abbrevations file required to name the azure resources.
 var abbrs = loadJsonContent('./abbreviations.json')
@@ -54,7 +55,17 @@ resource keyVault 'Microsoft.KeyVault/vaults@2022-07-01' existing = {
   name: keyVaultName
 }
 
-resource logAnalytics 'Microsoft.OperationalInsights/workspaces@2023-09-01' = {
+var useExisting = !empty(existingLogAnalyticsWorkspaceId)
+var existingLawSubscription = useExisting ? split(existingLogAnalyticsWorkspaceId, '/')[2] : ''
+var existingLawResourceGroup = useExisting ? split(existingLogAnalyticsWorkspaceId, '/')[4] : ''
+var existingLawName = useExisting ? split(existingLogAnalyticsWorkspaceId, '/')[8] : ''
+
+resource existingLogAnalyticsWorkspace 'Microsoft.OperationalInsights/workspaces@2023-09-01' existing = if (useExisting) {
+  name: existingLawName
+  scope: resourceGroup(existingLawSubscription, existingLawResourceGroup)
+}
+
+resource logAnalytics 'Microsoft.OperationalInsights/workspaces@2023-09-01' = if (!useExisting) {
   name: workspaceName
   location: location
   tags: {}
@@ -93,7 +104,7 @@ resource applicationInsights 'Microsoft.Insights/components@2020-02-02' = {
     Application_Type: 'web'
     publicNetworkAccessForIngestion: 'Enabled'
     publicNetworkAccessForQuery: 'Enabled'
-    WorkspaceResourceId: logAnalytics.id
+    WorkspaceResourceId: useExisting ? existingLogAnalyticsWorkspace.id : logAnalytics.id
   }
 }
 
@@ -490,5 +501,10 @@ output aiSearchService string = aiSearch.name
 output aiProjectName string = aiHubProject.name
 
 output applicationInsightsId string = applicationInsights.id
-output logAnalyticsWorkspaceResourceName string = logAnalytics.name
+output logAnalyticsWorkspaceResourceName string = useExisting ? existingLogAnalyticsWorkspace.name : logAnalytics.name
+output logAnalyticsWorkspaceResourceGroup string = useExisting ? existingLawResourceGroup : resourceGroup().name
+
+
 output storageAccountName string = storageNameCleaned
+output applicationInsightsConnectionString string = applicationInsights.properties.ConnectionString
+