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Train the trainers initial session feedback integration (#175)
## Purpose <!-- Describe the intention of the changes being proposed. What problem does it solve or functionality does it add? --> Integration changes to docs contents as a result of feedback from our initial Train the Trainers session on Feb 20. ## Does this introduce a breaking change? <!-- Mark one with an "x". --> ``` [ ] Yes [ x] No ``` ## Pull Request Type What kind of change does this Pull Request introduce? <!-- Please check the one that applies to this PR using "x". --> ``` [ ] Bugfix [ ] Feature [ ] Code style update (formatting, local variables) [ ] Refactoring (no functional changes, no api changes) [ x] Documentation content changes [ ] Other... Please describe: ``` ## How to Test Preview site available here: https://ronline-java-aca-preview.azurewebsites.net/
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cleanup.md

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1. Clean up the Azure OpenAI Service instance (optional).
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If you completed the optional [Lab 5]({% link docs/05_lab_openai/05_openlab_openai_aca.md %}), you created a new Azure OpenAI instance. Use the following command to delete it before you delete any other resources. If you didn't complete Lab 5, you can ignore this step.
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If you completed the optional [Lab 3]({% link docs/03_lab_openai/03_openlab_openai_aca.md %}), you created a new Azure OpenAI instance. Use the following command to delete it before you delete any other resources. If you didn't complete Lab 3, you can ignore this step.
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```bash
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az cognitiveservices account delete -g $RESOURCE_GROUP -n $OPEN_AI_SERVICE_NAME

docs/01_lab_plan/0101.md

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1. On your lab computer, open a web browser, go to [GitHub](https://github.com), and sign in to your GitHub account. If you don’t have a GitHub account, create one (go to [Join GitHub](https://github.com/join), and follow the instructions at [Signing up for a new GitHub account](https://docs.github.com/en/get-started/signing-up-for-github/signing-up-for-a-new-github-account)).
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1. Go to the [source folder of this lab’s GitHub repo](https://github.com/Azure-Samples/java-on-aca/tree/main/src), and review the **README.md file**.
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1. Learn how to run the application in dev environments. Pay particular attention to the readme sections that cover [starting services locally without Docker](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-without-docker), [starting services locally with docker-compose](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-with-docker-compose), and [starting services locally with docker-compose and Java](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-with-docker-compose-and-java). After you’ve configured your development environment, if time permits, consider launching the application locally using one of these methods.
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1. In the source folder of this lab’s GitHub repo, go to each folder that contains the code of the individual spring-petclinic-\* services and review the content.
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1. Review the instructions for manually running the application in your dev environment. Pay particular attention to the readme sections that cover [starting services locally without Docker](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-without-docker), [starting services locally with docker-compose](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-with-docker-compose), and [starting services locally with docker-compose and Java](https://github.com/Azure-Samples/java-on-aca/tree/main/src#starting-services-locally-with-docker-compose-and-java).
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{: .note }
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At this point, you **do not** need to run the app in your dev environment using these methods. Simply reviewing and understanding how you can use these instructions is sufficient for now. However, if you've got extra time after completing the rest of this lab, feel free to try launching the application and exploring its functionality locally.
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1. In the source folder of this lab’s GitHub repo, go to each folder that contains the code of the individual spring-petclinic-\* services and spend a few minutes reviewing the contents, familiarizing yourself with the overall code structure.
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![microservices overview](../../images/services.png)
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docs/02_lab_launch/0201.md

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## Step-by-step guidance
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1. In your lab environment, open a command-line environment (Windows Subsystem for Linux, Git Bash, PowerShell, or VS Code terminal) and sign in to your Azure subscription with the following command:
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{: .note }
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We'll be using Bash commands to complete this lab. You can use any compatible command-line environment, such as the Windows Subsystem for Linux, Git Bash, or the Visual Studio Code Bash terminal. To avoid potential errors, **do not** run these commands in a PowerShell session.
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1. In your lab environment, open a command-line environment and sign in to your Azure subscription with the following command:
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```bash
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az login

docs/02_lab_launch/0203.md

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> The server name must be globally unique, so if the randomly generated name is already in use, adjust it accordingly . Keep in mind that the name can contain only lowercase letters, numbers, and hyphens.
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{: .note }
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> For simplicity’s sake, in this lab, we’re using a MySQL admin password to allow apps to connect to MySQL Server. However, we don’t recommend this when operating in a production environment. For the secured managed identity solution, refer to [Lab 04: Connect to a database securely using managed identity]({% link docs/04_lab_secrets/04_openlab_secrets_aca.md %}).
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> For simplicity’s sake, in this lab, we’re using a MySQL admin password to allow apps to connect to MySQL Server. However, we don’t recommend this when operating in a production environment. For the secured managed identity solution, refer to [Lab 5: Connect to a database securely using managed identity]({% link docs/05_lab_secrets/05_openlab_secrets_aca.md %}).
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```bash
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MYSQL_SERVER_NAME=mysql-$APPNAME-$UNIQUEID
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---
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title: '1. Create an Azure OpenAI account (optional)'
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title: '1. Create an Azure OpenAI account (Optional)'
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layout: default
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nav_order: 1
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parent: 'Lab 5: Integrate Azure OpenAI Service with your apps'
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parent: 'Lab 3: Integrate Azure OpenAI Service with your apps'
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---
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# Create an Azure OpenAI account (optional)
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# Create an Azure OpenAI account (Optional)
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Before you can add AI capabilities to your application, you need to create an Azure OpenAI account and deploy the language models that you want to use.
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nav_order: 2
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nav_exclude: true
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parent: 'Lab 5: Integrate with Azure OpenAI'
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parent: 'Lab 3: Integrate with Azure OpenAI'
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---
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Deploy the sample ai servcie `chat-agent`, and explore the power of Azure Open AI service.
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---
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title: '3. Improve the chat service experience (optional)'
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title: '3. Improve the chat service experience (Optional)'
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layout: default
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nav_order: 6
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parent: 'Lab 5: Integrate Azure OpenAI Service with your apps'
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parent: 'Lab 3: Integrate Azure OpenAI Service with your apps'
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---
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# Improve the chat service experience (optional)
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# Improve the chat service experience (Optional)
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You’ve completed this lab’s step-by-step instructions and built a chatbot that integrates with the Sprint Petclinic application. The following optional sections can extend the chat service’s capabilities and improve how users interact with it.
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title: '4. Review'
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parent: 'Lab 5: Integrate Azure OpenAI Service with your apps'
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parent: 'Lab 3: Integrate Azure OpenAI Service with your apps'
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# Review
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The following diagram should reflect the current state of the deployed application.
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![lab 5 overview](../../images/acalab5.png)
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![lab 3 overview](../../images/acalab-openai.png)
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title: '2. Create AI application from scratch'
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parent: 'Lab 5: Integrate Azure OpenAI Service with your apps'
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parent: 'Lab 3: Integrate Azure OpenAI Service with your apps'
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# Create an AI application from scratch for the Petclinic workload
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- A GitHub Copilot subscription. (If you don’t already have a subscription, try [GitHub Copilot Free](https://docs.github.com/en/copilot/quickstart#sign-up-for-github-copilot).)
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- The [GitHub Copilot Chat extension](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot-chat) installed in your copy of Visual Studio Code.
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- A prepared Azure OpenAI instance with the `gpt-4o` model deployed. For more details, refer to the instructions [in previous section of this lab]({% link docs/05_lab_openai/0501.md %}).
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- A prepared Azure OpenAI instance with the `gpt-4o` model deployed. For more details, refer to the instructions [in previous section of this lab]({% link docs/03_lab_openai/0301.md %}).
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- The `endpoint` and `api-key` values for your Azure OpenAI instance. You can find these by going to your Azure OpenAI instance in the Azure portal and looking in the `Resource Management` \> `Keys and Endpoint` section.
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## Step by step guidance
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---
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title: 'Integrate AI to existing project'
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nav_order: 5
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parent: 'Lab 5: Integrate with Azure OpenAI'
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parent: 'Lab 3: Integrate Azure OpenAI Service with your apps'
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# Integrate AI into your existing project

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