Merge pull request #25 from Azure/miyagi-v2

Miyagi V2 - Semantic Kernel workshop - beta release

.devcontainer/devcontainer.json

@@ -0,0 +1,16 @@
+{
+    "image": "mcr.microsoft.com/devcontainers/universal:2",
+    "features": {
+        "ghcr.io/azure/azure-dev/azd:latest": {},
+        "ghcr.io/devcontainers/features/azure-cli:latest": {}
+    },
+    "customizations": {
+        "vscode": {
+            "extensions": [
+                "ms-dotnettools.csdevkit",
+                "EditorConfig.EditorConfig",
+                "GitHub.copilot"
+			]
+		}
+	}
+}

.gitignore

@@ -21,7 +21,6 @@ node_modules/
 parts/
 sdist/
 var/
-package*.json
 *.egg-info/
 .installed.cfg
 *.egg
@@ -69,3 +68,23 @@ ENV/
 # MkDocs documentation
 site*/
 .vscode/
+
+# Build results
+[Dd]ebug/
+[Dd]ebugPublic/
+[Rr]elease/
+[Rr]eleases/
+x64/
+x86/
+[Aa][Rr][Mm]/
+[Aa][Rr][Mm]64/
+bld/
+[Bb]in/
+[Oo]bj/
+[Ll]og/
+[Ll]ogs/
+
+# Frontend/react/npm files
+appsettings.json
+.env
+package-lock.json

docs/wksp/05-semantic-kernel-workshop/advanced-ai-orchestration/index.md

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+# Advanced AI Orchestration using agents and planners

docs/wksp/05-semantic-kernel-workshop/index.md

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+# Hands-on AI Orchestration using Semantic Kernel
+
+This workshop is broken into 2 main sections:
+
+1. [Create simple AI Orchestration using Sematic Kernel](simple-ai-orchestration/index.md)
+1. [Create advanced AI Orchestration using Sematik Kernel with agents and planners](advanced-ai-orchestration/index.md)

docs/wksp/05-semantic-kernel-workshop/simple-ai-orchestration/create-deployable-app/azd-infra.md

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+# Azure Developer CLI (AZD) and Bicep templates for Infrastructure as Code deployment
+
+In this section we go over the creation of `azd` [(Azure Developer CLI)]((https://aka.ms/azure-dev/install))
+files and corresponding bicep templates to be able to build, provision infrastructure and
+deploy our solution into Azure.
+
+## Azure Developer CLI files overview
+
+The following components are needed to deploy via AZD
+
+### `azure.yaml` file
+
+This file specifies the components to be deployed. Our file specifies two components to be deployed:
+
+1. Application backend - .NET deployed as Azure Container App
+1. Web frontend - Typescript deployed as Azure Container App
+
+For each component we need to provide the path to the corresponding `Dockerfile` which will be used
+to build and package the application:
+
+```yaml
+name: semantic-kernel-workshop-csharp
+metadata:
+  template: [email protected]
+services:
+  api:
+    project: ./App/backend/
+    host: containerapp
+    language: dotnet
+    docker:
+      path: ../Dockerfile
+      context: ../../
+  web:
+    project: ../frontend/
+    host: containerapp
+    language: ts
+    docker:
+      path: ./Dockerfile
+      context: ./
+```
+
+### `infra` directory
+
+Within the `infra` directory you have the option to provide either `bicep` or `terraform` templates
+to deploy the required infrastructure for our application to run. In this example we
+use `bicep` templates which are organized as follows:
+
+* **infra**
+  * `main.bicep` - contains the bicep parameters and modules to deploy
+  * `main.paramters.json` - parameter values to be used during deployment
+  * `abbreviations.json` - optional file to specify suffix abbreviations for each resource type
+    * app - subdirectory with application related templates
+      * `api.bicep` - bicep template for backend application infrastructure
+      * `web.bicep` - bicep templated for web application infrastructure
+    * core - subdirectory with templates for core infrastructure components
+      * **ai** - subdirectory for AI related components
+      * **host** - subdirectory for container app, environment and registry components
+      * **monitor** - subdirectory for monitoring components (e.g. application insights)
+      * **security** - subdirectory for security components (e.g. keyvault)
+      * **storage** - subdirectory for storage components (e.g. storage account)
+
+The `azd init` command can be used to generate a starter template, however the quickest way
+to generate an existing template is to find a template that uses similar components from
+[awesome-azd](https://azure.github.io/awesome-azd/).
+
+## Deploying using AZD CLI
+
+You can build, provision all resources and deploy by following these steps:
+
+1. Switch to `workshop/donet` directory.
+1. Ensure Docker desktop is running (if not using Github Codespace).
+1. Run `azd auth login` to login to your Azure account.
+1. Run `azd up` to provision Azure resources and deploy this sample to those resources.
+   You will be prompted for the following parameters:
+    * Environment name: sk-test
+    * Select an Azure subscription to use from list
+    * Select an Azure location to use: e.g. (US) East US 2 (eastus2)
+    * Enter a value for the infrastructure parameters:
+      * **openAIApiKey**
+      * **openAiChatGptDeployment**: e.g. gpt-4o
+      * **openAiEndpoint**
+      * **stockServiceApiKey**
+1. After the application has been successfully deployed you will see the API and Web Service URLs printed in the console.  
+   Click the Web Service URL to interact with the application in your browser.
+
+   **NOTE:** It may take a few minutes for the application to be fully  deployed.
+
+## Deployment removal
+
+In order to remove all resources deployed, use this command:
+
+```bash
+azd down --purge
+```