Migrate quickstarts to Extensions AI library (#43673)

* Migrate quickstarts to Extensions AI library



---------

Co-authored-by: Genevieve Warren <[email protected]>

Author: alexwolfmsft

docs/ai/quickstarts/get-started-openai.md

@@ -12,214 +12,146 @@ zone_pivot_groups: openai-library
 
 # Build an AI chat app with .NET
 
-<!-- markdownlint-disable MD044 -->
-:::zone target="docs" pivot="openai"
-<!-- markdownlint-enable MD044 -->
+In this quickstart, you learn how to create a conversational .NET console chat app using an OpenAI or Azure OpenAI model. The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI) library so you can write code using AI abstractions rather than a specific SDK. AI abstractions enable you to change the underlying AI model with minimal code changes.
+
+> [!NOTE]
+> The [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) library is currently in Preview.
 
-Get started with OpenAI and [Semantic Kernel](../semantic-kernel-dotnet-overview.md) by creating a simple .NET 8 console chat application. The application will run locally and use the OpenAI `gpt-3.5-turbo` model. Follow these steps to get access to OpenAI and learn how to use Semantic Kernel.
+:::zone target="docs" pivot="openai"
 
-[!INCLUDE [download-alert](includes/prerequisites-openai.md)]
+[!INCLUDE [openai-prereqs](includes/prerequisites-openai.md)]
 
 :::zone-end
 
-<!-- markdownlint-disable MD044 -->
 :::zone target="docs" pivot="azure-openai"
-<!-- markdownlint-enable MD044 -->
 
-Get started with OpenAI and [Semantic Kernel](../semantic-kernel-dotnet-overview.md) by creating a simple .NET 8 console chat application. The application will run locally and connect to the OpenAI `gpt-35-turbo` model deployed into Azure OpenAI. Follow these steps to provision Azure OpenAI and learn how to use Semantic Kernel.
-
-[!INCLUDE [download-alert](includes/prerequisites-azure-openai.md)]
+[!INCLUDE [azure-openai-prereqs](includes/prerequisites-azure-openai.md)]
 
 :::zone-end
 
-## Get the sample project
+[!INCLUDE [semantic-kernel](../../azure/includes/semantic-kernel.md)]
 
 [!INCLUDE [clone-sample-repo](includes/clone-sample-repo.md)]
 
-:::zone target="docs" pivot="azure-openai"
+## Create the app
 
-## Create the Azure OpenAI service
+Complete the following steps to create a .NET console app to connect to an AI model.
 
-# [Azure Developer CLI](#tab/azd)
+1. In an empty directory on your computer, use the `dotnet new` command to create a new console app:
 
-[!INCLUDE [deploy-azd](includes/deploy-azd.md)]
+    ```dotnetcli
+    dotnet new console -o ChatAppAI
+    ```
 
-# [Azure CLI](#tab/azure-cli)
+1. Change directory into the app folder:
 
-1. To provision an Azure OpenAI service and model using the Azure CLI, complete the steps in the [Create and deploy an Azure OpenAI Service resource](/azure/ai-services/openai/how-to/create-resource?pivots=cli) article.
+    ```dotnetcli
+    cd ChatAppAI
+    ```
 
-1. From a terminal or command prompt, navigate to the `src\quickstarts\azure-openai\semantic-kernel\02-HikerAI` directory.
+1. Install the required packages:
 
-1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
+    :::zone target="docs" pivot="azure-openai"
 
     ```bash
-    dotnet user-secrets init
-    dotnet user-secrets set OpenAIKey <your-openai-key>
-
-# [Azure Portal](#tab/azure-portal)
-
-1. To provision an Azure OpenAI service and model using the Azure portal, complete the steps in the [Create and deploy an Azure OpenAI Service resource](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) article.
+    dotnet add package Azure.Identity
+    dotnet add package Azure.AI.OpenAI
+    dotnet add package Microsoft.Extensions.AI.OpenAI
+    dotnet add package Microsoft.Extensions.Configuration
+    dotnet add package Microsoft.Extensions.Configuration.UserSecrets
+    ```
 
-1. From a terminal or command prompt, navigate to the `src\quickstarts\azure-openai\semantic-kernel\02-HikerAI` directory.
+    :::zone-end
 
-1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
+    :::zone target="docs" pivot="openai"
 
     ```bash
-    dotnet user-secrets init
-    dotnet user-secrets set OpenAIKey <your-openai-key>
-
----
-
-:::zone-end
-
-## Try the HikerAI sample
-
-<!-- markdownlint-disable MD029 MD044 -->
-:::zone target="docs" pivot="openai"
+    dotnet add package OpenAI
+    dotnet add package Microsoft.Extensions.AI.OpenAI
+    dotnet add package Microsoft.Extensions.Configuration
+    dotnet add package Microsoft.Extensions.Configuration.UserSecrets
+    ```
 
-1. From a terminal or command prompt, navigate to the `src\quickstarts\azure-openai\semantic-kernel\02-HikerAI` directory.
+    :::zone-end
 
-1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
+1. Open the app in Visual Studio Code (or your editor of choice).
 
     ```bash
-    dotnet user-secrets init
-    dotnet user-secrets set OpenAIKey <your-openai-key>
-    ```
-
-1. Use the `dotnet run` command to run the app:
-
-    ```dotnetcli
-    dotnet run
+    code .
     ```
 
-:::zone-end
-
 :::zone target="docs" pivot="azure-openai"
 
-1. From a terminal or command prompt, navigate to the `semantic-kernel\02-HikerAI` directory.
-
-2. Use the `dotnet run` command to run the app:
-
-    ```dotnetcli
-    dotnet run
-    ```
-
-    > [!TIP]
-    > If you get an error message, the Azure OpenAI resources might not have finished deploying. Wait a couple of minutes and try again.
+[!INCLUDE [create-ai-service](includes/create-ai-service.md)]
 
 :::zone-end
 
 :::zone target="docs" pivot="openai"
 
-## Explore the code
-
-The app uses the [`Microsoft.SemanticKernel`](https://www.nuget.org/packages/Microsoft.SemanticKernel) package to send and receive requests to the OpenAI service.
+## Configure the app
 
-The app code is contained within the **Program.cs** file. The first several lines of code set configuration values and get the OpenAI Key that was previously set using the `dotnet user-secrets` command.
+1. Navigate to the root of your .NET project from a terminal or command prompt.
 
-```csharp
-var config = new ConfigurationBuilder().AddUserSecrets<Program>().Build();
-string model = "gpt-3.5-turbo";
-string key = config["OpenAIKey"];
-```
-
-The `OpenAIChatCompletionService` service facilitates the requests and responses.
+1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
 
-```csharp
-// Create the OpenAI Chat Completion Service
-OpenAIChatCompletionService service = new(model, key);
-```
+    ```bash
+    dotnet user-secrets init
+    dotnet user-secrets set OpenAIKey <your-openai-key>
+    dotnet user-secrets set ModelName <your-openai-model-name>
+    ```
 
 :::zone-end
 
-<!-- markdownlint-disable MD044 -->
-:::zone target="docs" pivot="azure-openai"
-<!-- markdownlint-enable MD044 -->
+## Add the app code
 
-## Explore the code
+The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) package to send and receive requests to the AI model and is designed to provide users with information about hiking trails.
 
-The application uses the [`Microsoft.SemanticKernel`](https://www.nuget.org/packages/Microsoft.SemanticKernel) package to send and receive requests to an Azure OpenAI service deployed in Azure.
+1. In the **Program.cs** file, add the following code to connect and authenticate to the AI model.
 
-The entire application is contained within the **Program.cs** file. The first several lines of code retrieve the secrets and configuration values that were set in the `dotnet user-secrets` for you during the application provisioning.
+    :::zone target="docs" pivot="azure-openai"
 
-```csharp
-// Retrieve the local secrets saved during the Azure deployment
-var config = new ConfigurationBuilder().AddUserSecrets<Program>().Build();
-string endpoint = config["AZURE_OPENAI_ENDPOINT"];
-string deployment = config["AZURE_OPENAI_GPT_NAME"];
-```
+    :::code language="csharp" source="snippets/build-chat-app/azure-openai/program.cs" range="1-12":::
 
-The `AzureOpenAIChatCompletionService` service facilitates the requests and responses.
+    > [!NOTE]
+    > <xref:Azure.Identity.DefaultAzureCredential> searches for authentication credentials from your local tooling. If you aren't using the `azd` template to provision the Azure OpenAI resource, you'll need to assign the `Azure AI Developer` role to the account you used to sign in to Visual Studio or the Azure CLI. For more information, see [Authenticate to Azure AI services with .NET](../azure-ai-services-authentication.md).
 
-```csharp
-// Create the Azure OpenAI Chat Completion Service
-AzureOpenAIChatCompletionService service = new(deployment, endpoint, new DefaultAzureCredential());
-```
+    :::zone-end
 
-:::zone-end
+    :::zone target="docs" pivot="openai"
 
-Add a system prompt to provide more context to the model, which influences model behavior and the generated completions during the conversation.
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="1-11":::
 
-```csharp
-// Start the conversation with context for the AI model
-ChatHistory chatHistory = new("""
-    You are a hiking enthusiast who helps people discover fun hikes in their area. 
-    You are upbeat and friendly. You introduce yourself when first saying hello.
-    When helping people out, you always ask them for this information
-    to inform the hiking recommendation you provide:
+    :::zone-end
 
-    1. Where they are located
-    2. What hiking intensity they are looking for
+1. Create a system prompt to provide the AI model with initial role context and instructions about hiking recommendations:
 
-    You will then provide three suggestions for nearby hikes that vary in length
-    after you get that information. You will also share an interesting fact about
-    the local nature on the hikes when making a recommendation.
-    """);
-```
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="13-30":::
 
-Add a user message to the chat history using the `AddUserMessage` function. Use the `GetChatMessageContentAsync` function to instruct the model to generate a response based off the system prompt and the user request.
+1. Create a conversational loop that accepts an input prompt from the user, sends the prompt to the model, and prints the response completion:
 
-```csharp
-
-// Add user message to chat history
-chatHistory.AddUserMessage("Hi! Apparently you can help me find a hike that I will like?");
-
-// Print User Message to console
-Console.WriteLine($"{chatHistory.Last().Role} >>> {chatHistory.Last().Content}");
-
-// Get response
-var response = await service.GetChatMessageContentAsync(
-    chatHistory, new OpenAIPromptExecutionSettings() { MaxTokens = 400 });
-```
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="32-51":::
 
-Add the response from the mode to maintain the chat history.
-
-```csharp
-// Add response to chat history
-chatHistory.Add(response);
+1. Use the `dotnet run` command to run the app:
 
-// Print Response to console
-Console.WriteLine($"{chatHistory.Last().Role} >>> {chatHistory.Last().Content}");
-```
+    ```dotnetcli
+    dotnet run
+    ```
 
-Customize the system prompt and user message to see how the model responds to help you find a hike that you'll like.
+    The app prints out the completion response from the AI model. Send additional follow up prompts and ask other questions to experiment with the AI chat functionality.
 
-<!-- markdownlint-disable MD044 -->
 :::zone target="docs" pivot="azure-openai"
-<!-- markdownlint-enable MD044 -->
+
 ## Clean up resources
 
-Remove the corresponding deployment and all resources when you no longer need the sample application or resources.
+When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
 
 ```azdeveloper
 azd down
 ```
 
-[!INCLUDE [troubleshoot](includes/troubleshoot.md)]
-
 :::zone-end
 
 ## Next steps
 
-- [Quickstart - Get insight about your data from .NET AI chat app](quickstart-ai-chat-with-data.md)
-- [Generate text and conversations with .NET and OpenAI Completions](/training/modules/open-ai-dotnet-text-completions/)
+- [Quickstart - Chat with a local AI model](quickstart-local-ai.md)
+- [Generate images using AI with .NET](quickstart-openai-generate-images.md)

docs/ai/quickstarts/includes/clone-sample-repo.md

@@ -7,7 +7,7 @@ ms.topic: include
 
 ## Clone the sample repository
 
- You can create your own app and follow along the steps in the sections ahead, or you can clone the GitHub repository that contains the completed sample apps for all of the quickstarts. The sample repo is also structured as an Azure Developer CLI template that can provision an Azure OpenAI resource for you.
+ You can create your own app using the steps in the sections ahead, or you can clone the GitHub repository that contains the completed sample apps for all of the quickstarts. If you plan to use Azure OpenAI, the sample repo is also structured as an Azure Developer CLI template that can provision an Azure OpenAI resource for you.
 
 ```bash
 git clone https://github.com/dotnet/ai-samples.git

docs/ai/quickstarts/includes/create-ai-service.md

@@ -10,7 +10,7 @@
 
 1. From a terminal or command prompt, navigate to the root of your project directory.
 
-1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
+1. Run the following commands to configure your Azure OpenAI endpoint and model name for the sample app:
 
     ```bash
     dotnet user-secrets init
@@ -24,7 +24,7 @@
 
 1. From a terminal or command prompt, navigate to the root of your project directory.
 
-1. Run the following commands to configure your OpenAI API key as a secret for the sample app:
+1. Run the following commands to configure your Azure OpenAI endpoint and model name for the sample app:
 
     ```bash
     dotnet user-secrets init