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‎articles/azure-app-configuration/quickstart-chat-completion-dotnet.md

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@@ -19,7 +19,7 @@ In this quickstart you will create a .NET console app that retrieves chat comple
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## Prerequisites
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config#create-a-chat-completion-configuration).
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config.md#create-a-chat-completion-configuration).
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- [.NET SDK 6.0 or later](https://dotnet.microsoft.com/download)
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## Create a console app
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1. Open the _Program.cs_, and add the following namespaces at the top of the file:
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```csharp
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using Microsoft.Extensions.Configuration;
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using Azure.Identity;
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using Azure.AI.OpenAI;
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using OpenAI.Chat;
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using Microsoft.Extensions.Configuration;
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using Azure.Identity;
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using Azure.AI.OpenAI;
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using OpenAI.Chat;
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```
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1. Connect to your App Configuration store by calling the `AddAzureAppConfiguration` method in the _Program.cs_ file.
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You can connect to App Configuration using **Microsoft Entra ID (recommended)**, or a connection string. In this example, you use Microsoft Entra ID, the `DefaultAzureCredential` to authenticate to your App Configuration store. Follow the [instructions](./concept-enable-rbac.md#authentication-with-token-credentials) to assign your credential the **App Configuration Data Reader** role. Be sure to allow sufficient time for the permission to propagate before running your application.
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```csharp
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var credential = new DefaultAzureCredential();
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var credential = new DefaultAzureCredential();
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IConfiguration configuration = new ConfigurationBuilder()
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.AddAzureAppConfiguration(options =>
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{
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string endpoint = Environment.GetEnvironmentVariable("AZURE_APPCONFIG_ENDPOINT");
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IConfiguration configuration = new ConfigurationBuilder()
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.AddAzureAppConfiguration(options =>
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{
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string endpoint = Environment.GetEnvironmentVariable("AZURE_APPCONFIG_ENDPOINT");
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options.Connect(new Uri(endpoint), credential);
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}).Build();
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options.Connect(new Uri(endpoint), credential);
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}).Build();
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var model = configuration.GetSection("ChatLLM:Model")["model"];
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string modelEndpoint = configuration.GetSection("ChatLLM:Endpoint").Value;
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var model = configuration.GetSection("ChatLLM:Model")["model"];
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string modelEndpoint = configuration.GetSection("ChatLLM:Endpoint").Value;
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Console.WriteLine($"Hello, I am your AI assistant powered by Azure App Configuration ({model})");
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Console.WriteLine($"Hello, I am your AI assistant powered by Azure App Configuration ({model})");
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```
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1. Create an instance of the `AzureOpenAIClient`. Use the existing instance of `DefaultAzureCredential` we created in the previous step to authenticate to your Azure OpenAI resource. Assign your credential the [Cognitive Services OpenAI User](../role-based-access-control/built-in-roles/ai-machine-learning.md#cognitive-services-openai-user) or [Cognitive Services OpenAI Contributor](../role-based-access-control/built-in-roles/ai-machine-learning.md#cognitive-services-openai-contributor). For detailed steps, see [Role-based access control for Azure OpenAI service](/azure/ai-services/openai/how-to/role-based-access-control). Be sure to allow sufficient time for the permission to propagate before running your application.
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```csharp
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// Existing code to connect to your App configuration store
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// ...
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// Existing code to connect to your App configuration store
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// ...
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// Initialize the AzureOpenAIClient
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AzureOpenAIClient client = new AzureOpenAIClient(new Uri(modelEndpoint), credential);
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ChatClient chatClient = client.GetChatClient(model);
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// Initialize the AzureOpenAIClient
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AzureOpenAIClient client = new AzureOpenAIClient(new Uri(modelEndpoint), credential);
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ChatClient chatClient = client.GetChatClient(model);
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```
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1. Next will update the existing code in _Program.cs_ file to configure the chat completion options:
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```csharp
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...
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// Existing code to initialize the AzureOpenAIClient
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// Configure chat completion options
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ChatCompletionOptions options = new ChatCompletionOptions
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{
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Temperature = float.Parse(configuration.GetSection("ChatLLM:Model")["temperature"]),
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MaxOutputTokenCount = int.Parse(configuration.GetSection("ChatLLM:Model")["max_tokens"]),
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TopP = float.Parse(configuration.GetSection("ChatLLM:Model")["top_p"])
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};
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...
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// Existing code to initialize the AzureOpenAIClient
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// Configure chat completion options
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ChatCompletionOptions options = new ChatCompletionOptions
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{
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Temperature = float.Parse(configuration.GetSection("ChatLLM:Model")["temperature"]),
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MaxOutputTokenCount = int.Parse(configuration.GetSection("ChatLLM:Model")["max_tokens"]),
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TopP = float.Parse(configuration.GetSection("ChatLLM:Model")["top_p"])
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};
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```
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1. Update the _Program.cs_ file to add a helper method `GetChatMessages` to process chat messages:
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```csharp
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// Helper method to convert configuration messages to chat API format
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IEnumerable<ChatMessage> GetChatMessages()
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{
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var chatMessages = new List<ChatMessage>();
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// Helper method to convert configuration messages to chat API format
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IEnumerable<ChatMessage> GetChatMessages()
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{
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var chatMessages = new List<ChatMessage>();
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foreach (IConfiguration configuration in configuration.GetSection("ChatLLM:Model:messages").GetChildren())
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foreach (IConfiguration configuration in configuration.GetSection("ChatLLM:Model:messages").GetChildren())
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{
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switch (configuration["role"])
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{
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switch (configuration["role"])
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{
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case "system":
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chatMessages.Add(ChatMessage.CreateSystemMessage(configuration["content"]));
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break;
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case "user":
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chatMessages.Add(ChatMessage.CreateUserMessage(configuration["content"]));
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break;
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}
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case "system":
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chatMessages.Add(ChatMessage.CreateSystemMessage(configuration["content"]));
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break;
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case "user":
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chatMessages.Add(ChatMessage.CreateUserMessage(configuration["content"]));
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break;
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}
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return chatMessages;
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}
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return chatMessages;
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}
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```
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1. Update the code in the _Program.cs_ file to call the helper method `GetChatMessages` and pass the ChatMessages to the `CompleteChatAsync` method:
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```csharp
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...
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// Existing code to configure chat completion options
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//
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IEnumerable<ChatMessage> messages = GetChatMessages();
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// CompleteChatAsync method generates a completion for the given chat
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ChatCompletion completion = await chatClient.CompleteChatAsync(messages, options);
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Console.WriteLine("-------------------Model response--------------------------");
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Console.WriteLine(completion.Content[0].Text);
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Console.WriteLine("-----------------------------------------------------------");
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...
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...
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// Existing code to configure chat completion options
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//
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IEnumerable<ChatMessage> messages = GetChatMessages();
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// CompleteChatAsync method generates a completion for the given chat
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ChatCompletion completion = await chatClient.CompleteChatAsync(messages, options);
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Console.WriteLine("-------------------Model response--------------------------");
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Console.WriteLine(completion.Content[0].Text);
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Console.WriteLine("-----------------------------------------------------------");
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...
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```
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1. After completing the previous steps, your _Program.cs_ file should now contain the complete implementation as shown below:
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```c#
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using Microsoft.Extensions.Configuration;
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using Azure.Identity;
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using Azure.AI.OpenAI;
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using OpenAI.Chat;
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using Microsoft.Extensions.Configuration;
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using Azure.Identity;
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using Azure.AI.OpenAI;
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using OpenAI.Chat;
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var credential = new DefaultAzureCredential();
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var credential = new DefaultAzureCredential();
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IConfiguration configuration = new ConfigurationBuilder()
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.AddAzureAppConfiguration(options =>
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{
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string endpoint = Environment.GetEnvironmentVariable("AZURE_APPCONFIG_ENDPOINT");
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IConfiguration configuration = new ConfigurationBuilder()
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.AddAzureAppConfiguration(options =>
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{
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string endpoint = Environment.GetEnvironmentVariable("AZURE_APPCONFIG_ENDPOINT");
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options.Connect(new Uri(endpoint), credential);
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options.Connect(new Uri(endpoint), credential);
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}).Build();
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}).Build();
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var model = configuration.GetSection("ChatLLM:Model")["model"];
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string modelEndpoint = configuration.GetSection("ChatLLM:Endpoint").Value;
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var model = configuration.GetSection("ChatLLM:Model")["model"];
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string modelEndpoint = configuration.GetSection("ChatLLM:Endpoint").Value;
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// Initialize the AzureOpenAIClient
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AzureOpenAIClient client = new AzureOpenAIClient(new Uri(modelEndpoint), credential);
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ChatClient chatClient = client.GetChatClient(model);
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// Initialize the AzureOpenAIClient
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AzureOpenAIClient client = new AzureOpenAIClient(new Uri(modelEndpoint), credential);
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ChatClient chatClient = client.GetChatClient(model);
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// Configure chat completion options
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ChatCompletionOptions options = new ChatCompletionOptions
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{
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Temperature = float.Parse(configuration.GetSection("ChatLLM:Model")["temperature"]),
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MaxOutputTokenCount = int.Parse(configuration.GetSection("ChatLLM:Model")["max_tokens"]),
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TopP = float.Parse(configuration.GetSection("ChatLLM:Model")["top_p"])
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};
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IEnumerable<ChatMessage> messages = GetChatMessages();
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// Configure chat completion options
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ChatCompletionOptions options = new ChatCompletionOptions
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{
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Temperature = float.Parse(configuration.GetSection("ChatLLM:Model")["temperature"]),
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MaxOutputTokenCount = int.Parse(configuration.GetSection("ChatLLM:Model")["max_tokens"]),
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TopP = float.Parse(configuration.GetSection("ChatLLM:Model")["top_p"])
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};
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IEnumerable<ChatMessage> messages = GetChatMessages();
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ChatCompletion completion = await chatClient.CompleteChatAsync(messages, options);
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Console.WriteLine($"Hello, I am your AI assistant powered by Azure App Configuration ({model})");
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ChatCompletion completion = await chatClient.CompleteChatAsync(messages, options);
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Console.WriteLine($"Hello, I am your AI assistant powered by Azure App Configuration ({model})");
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Console.WriteLine("-------------------Model response--------------------------");
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Console.WriteLine(completion.Content[0].Text);
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Console.WriteLine("-----------------------------------------------------------");
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Console.WriteLine("-------------------Model response--------------------------");
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Console.WriteLine(completion.Content[0].Text);
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Console.WriteLine("-----------------------------------------------------------");
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IEnumerable<ChatMessage> GetChatMessages()
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{
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var chatMessages = new List<ChatMessage>();
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IEnumerable<ChatMessage> GetChatMessages()
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{
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var chatMessages = new List<ChatMessage>();
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foreach (IConfiguration configuration in configuration.GetSection("ChatLLM:Model:messages").GetChildren())
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foreach (IConfiguration configuration in configuration.GetSection("ChatLLM:Model:messages").GetChildren())
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{
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switch (configuration["role"])
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{
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switch (configuration["role"])
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{
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case "system":
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chatMessages.Add(ChatMessage.CreateSystemMessage(configuration["content"]));
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break;
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case "user":
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chatMessages.Add(ChatMessage.CreateUserMessage(configuration["content"]));
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break;
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}
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case "system":
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chatMessages.Add(ChatMessage.CreateSystemMessage(configuration["content"]));
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break;
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case "user":
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chatMessages.Add(ChatMessage.CreateUserMessage(configuration["content"]));
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break;
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}
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return chatMessages;
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}
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return chatMessages;
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}
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```
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## Build and run the app locally
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```Output
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Hello, I am your AI assistant powered by Azure App Configuration (gpt-4o)
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-------------------Model response--------------------------
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Good heavens! A pocket-sized contraption combining telegraph, camera, library, and more—instant communication and knowledge at one’s fingertips! Astonishing!
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-----------------------------------------------------------

‎articles/azure-app-configuration/quickstart-chat-completion-javascript.md

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## Prerequisites
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config#create-a-chat-completion-configuration).
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config.md#create-a-chat-completion-configuration).
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- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule). For information about installing Node.js either directly on Windows or using the Windows Subsystem for Linux (WSL), see [Get started with Node.js](/windows/dev-environment/javascript/nodejs-overview)
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```
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1. Create a file named app.js in the *app-config-chat-completion* directory and import the required packages:
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```javascript
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const { load } = require("@azure/app-configuration-provider");
5152
const { DefaultAzureCredential, getBearerTokenProvider } = require("@azure/identity");
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```
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1. Next will update the existing code in _app.js_ file to configure the chat completion options:
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```javascript
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// Existing code to initialize the AzureOpenAIClient
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const client = new AzureOpenAI({
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```
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1. After the environment variable is properly set, run the following command to run the app locally:
194-
``` bash
196+
```bash
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node app.js
196198
```
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You should see the following output:
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```Output
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Hello, I am your AI assistant powered by Azure App Configuration (gpt-4o)
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202205
-------------------Model response--------------------------
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Good heavens! A pocket-sized contraption combining telegraph, camera, library, and more—instant communication and knowledge at one’s fingertips! Astonishing!
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-----------------------------------------------------------

‎articles/azure-app-configuration/quickstart-chat-completion-python.md

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## Prerequisites
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config#create-a-chat-completion-configuration).
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- Complete the tutorial to [Create a chat completion configuration](./howto-chat-completion-config.md#create-a-chat-completion-configuration).
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- Python 3.8 or later - for information on setting up Python on Windows, see the [Python on Windows documentation](/windows/python/)
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## Create a python app
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```Output
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Hello, I am your AI assistant powered by Azure App Configuration (gpt-4o)
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-------------------Model response--------------------------
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Good heavens! A pocket-sized contraption combining telegraph, camera, library, and more—instant communication and knowledge at one’s fingertips! Astonishing!
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-----------------------------------------------------------

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