Harjit managed app

backend/tests/integration/test_api_index_configuration.py

@@ -0,0 +1,33 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+"""
+Integration tests for the /index/config API endpoints.
+"""
+
+from unittest.mock import AsyncMock, patch
+
+import pytest_asyncio
+
+
+@pytest_asyncio.fixture
+def mock_generate_indexing_prompts():
+    with patch(
+        "graphrag.api.generate_indexing_prompts", new_callable=AsyncMock
+    ) as mock:
+        mock.return_value = (
+            "synthetic-prompt1",
+            "synthetic-prompt2",
+            "synthetic-prompt3",
+        )
+        yield mock
+
+
+def test_generate_prompts(
+    blob_with_data_container_name, mock_generate_indexing_prompts, client
+):
+    """Test generating prompts."""
+    response = client.get(
+        "/index/config/prompts",
+        params={"storage_name": blob_with_data_container_name},
+    )
+    assert response.status_code == 200

infra/README.md

@@ -0,0 +1,53 @@
+# Managed App Instructions
+
+This guide is a temporary document that walks through the process to convert the graphrag solution accelerator to a managed app.
+
+ ### Prerequisites
+ ### 1. create a ACR and push the code to a docker image.
+ ### 2. This managed app uses storage account to deploy, so please copy the storage account name and the SAS key.
+ ### 3. When publishing the managed app , please turn on anon access to the Blob where the package can be accessed. 
+
+ ### Steps to build Managed App
+
+### 1. Auto format the bicep code
+
+As a precaution, start by auto-formating and linting the bicep code to detect any mistakes early-on.
+
+```bash
+cd <repo_root_directory>/infra
+find . -type f -name "*.bicep" -exec az bicep format --file {} \;
+find . -type f -name "*.bicep" -exec az bicep lint --file {} \;
+```
+
+### 2. Convert bicep -> ARM
+```bash
+az bicep build --file main.bicep --outfile managed-app/mainTemplate.json
+```
+
+### 3. Create & test the Azure portal interface
+
+Use the [Azure Portal Sandbox](https://portal.azure.com/#blade/Microsoft_Azure_CreateUIDef/SandboxBlade) to test and make any UI changes that are defined in [createUiDefinition.json](createUiDefinition.json). To make additional changes to the Azure portal experience, start by reading some [documentation](https://learn.microsoft.com/en-us/azure/azure-resource-manager/managed-applications/create-uidefinition-overview) and copying the contents of `createUiDefinition.json` into the sandbox environment.
+
+### 4. Package up the managed app code
+
+The name of the final two files (`mainTemplate.json` and `createUiDefinition.json`) cannot be changed. The file names are also case-sensitive and cannot be changed at this time. Managed apps require these files to be packaged up into a zip file (where the json files must be at the root directory).
+
+```bash
+cd <repo_root_directory>/infra/managed-app
+ tar -a -c -f managed-app.zip createUiDefinition.json mainTemplate.json openapi.json artifacts 
+ ```
+
+This zip file can then be uploaded to an Azure Storage location when setting up a [Service Catalog Managed Application Definition](https://ms.portal.azure.com/#view/Microsoft_Azure_Marketplace/GalleryItemDetailsBladeNopdl/id/Microsoft.ApplianceDefinition/selectionMode~/false/resourceGroupId//resourceGroupLocation//dontDiscardJourney~/false/selectedMenuId/home/launchingContext~/%7B%22galleryItemId%22%3A%22Microsoft.ApplianceDefinition%22%2C%22source%22%3A%5B%22GalleryFeaturedMenuItemPart%22%2C%22VirtualizedTileDetails%22%5D%2C%22menuItemId%22%3A%22home%22%2C%22subMenuItemId%22%3A%22Search%20results%22%2C%22telemetryId%22%3A%2220409084-39a1-4800-bbce-d0b26a6f46a4%22%7D/searchTelemetryId/d7d20e05-ca16-47f7-bed5-9c7b8d2fa641).
+
+### 5. Create the Service Catalog Managed App Definition
+
+In the Azure Portal, go to Marketplace and create a `Service Catalog Managed App Definition`. You must provide a uri link to the uploaded `managed-app.zip` file as part of the creation process.
+
+### 6. Deploy the managed app
+
+
+You can deploy from the portal using the following steps In the Azure Portal, find and click on the managed app definition resource that was created in the previous step. A button option to `Deploy from definition` will be available. Click on it and proceed through the setup steps (defined by the `createUiDefinitions.json` file) that a consumer would experience when installing the managed app.
+
+
+or you can deploy to azure [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure-Samples%2Fgraphrag-accelerator%2Frefs%2Fheads%2Fharjit-managed-app%2Finfra%2FmainTemplate.json)
+

infra/core/aks/aks.bicep

@@ -65,7 +65,7 @@ resource aks 'Microsoft.ContainerService/managedClusters@2024-09-02-preview' = {
   }
   properties: {
     enableRBAC: true
-    disableLocalAccounts: true
+    disableLocalAccounts: false
     dnsPrefix: !empty(dnsPrefix) ? dnsPrefix : toLower(clusterName)
     aadProfile: {
       managed: true

infra/core/aoai/aoai.bicep

@@ -0,0 +1,80 @@
+@description('Name of the Azure OpenAI instance')
+param openAiName string = 'openai${uniqueString(resourceGroup().id)}'
+
+@description('Location for the Azure OpenAI instance')
+param location string = resourceGroup().location
+
+@description('LLM model name')
+param llmModelName string = 'gpt-4o'
+
+@description('LLM Model API version')
+param llmModelVersion string
+
+@description('Embedding model name')
+param embeddingModelName string = 'text-embedding-ada-002'
+
+@description('Embedding Model API version')
+param embeddingModelVersion string
+
+@description('TPM quota for llm model deployment (x1000)')
+param llmTpmQuota int = 1
+
+@description('TPM quota for embedding model deployment (x1000)')
+param embeddingTpmQuota int = 1
+
+resource aoai 'Microsoft.CognitiveServices/accounts@2024-10-01' = {
+  name: openAiName
+  location: location
+  sku: {
+    name: 'S0'
+  }
+  kind: 'OpenAI'
+  properties: {
+    publicNetworkAccess: 'Enabled'
+    disableLocalAuth: true
+  }
+}
+
+resource llmDeployment 'Microsoft.CognitiveServices/accounts/deployments@2024-10-01' = {
+  parent: aoai
+  name: llmModelName
+  sku: {
+    name: 'GlobalStandard'
+    capacity: llmTpmQuota
+  }
+  properties: {
+    model: {
+      format: 'OpenAI'
+      name: llmModelName
+      version: llmModelVersion
+    }
+    currentCapacity: llmTpmQuota
+  }
+}
+
+resource embeddingDeployment 'Microsoft.CognitiveServices/accounts/deployments@2024-10-01' = {
+  parent: aoai
+  name: embeddingModelName
+  // NOTE: simultaneous model deployments are not supported at this time. As a workaround, use dependsOn to force the models to be deployed in a sequential manner.
+  dependsOn: [llmDeployment]
+  sku: {
+    name: 'Standard'
+    capacity: embeddingTpmQuota
+  }
+  properties: {
+    model: {
+      format: 'OpenAI'
+      name: embeddingModelName
+      version: embeddingModelVersion
+    }
+    currentCapacity: embeddingTpmQuota
+  }
+}
+
+output openAiEndpoint string = aoai.properties.endpoint
+output llmModel string = llmDeployment.properties.model.name
+output llmModelDeploymentName string = llmDeployment.name
+output llmModelApiVersion string = llmDeployment.apiVersion
+output textEmbeddingModel string = embeddingDeployment.properties.model.name
+output textEmbeddingModelDeploymentName string = embeddingDeployment.name
+output textEmbeddingModelApiVersion string = embeddingDeployment.apiVersion

infra/core/apim/apim.graphrag-servicedef.bicep

@@ -5,6 +5,9 @@ param backendUrl string
 param name string
 param apimname string
 
+
+
+
 resource api 'Microsoft.ApiManagement/service/apis@2023-09-01-preview' = {
   name: '${apimname}/${name}'
   properties: {
@@ -24,7 +27,7 @@ resource api 'Microsoft.ApiManagement/service/apis@2023-09-01-preview' = {
     }
     isCurrent: true
     format: 'openapi+json'
-    value: string(loadJsonContent('graphrag-openapi.json')) // local file will be dynamically created by deployment script
+    value: string(loadJsonContent('../../managed-app/openapi.json')) // local file will be dynamically created by deployment script
   }
   resource apiPolicy 'policies@2022-08-01' = {
     name: 'policy'