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Challenge 03 - Start coding with Azure OpenAI SDK and Inference SDK.

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Introduction

After completing the prompt flow challenge, it's time to start investigating, how you can write code to utilize the AI services.

The Azure OpenAI SDK is a set of client libraries that allows developers to interact with Azure Open AI models. This service provides access to powerful Open AI foundational models, with the security and enterprise capabilities of Azure.

Additionally, the Azure AI model inference SDK provides another option for interacting with AI models. This SDK simplifies the process of integrating AI capabilities into applications by providing a unified interface for interacting with different models.

Two Options Available:

  1. Azure OpenAI SDK: This SDK is designed for interacting with OpenAI models hosted on Azure, providing features like chat completions, embeddings, and more.
  2. Azure AI Model Inference SDK: This SDK is focused on running inferences using AI models, providing a streamlined way to get predictions and results from models.It offers access to powerful models from leading providers like OpenAI, Microsoft, Meta, and more.

Description

Now you’ll dive into .NET Core development by creating a simple console application and use your own data with Azure OpenAI models created in previous challenge.

You can also use the Azure Open AI SDK of another programming language of your preference.

The following example demonstrates the use of the Azure Open AI SDK. Alternatively, you can use the Inference SDK.

In a console window use the dotnet new command to create a new console app.

dotnet new console -n azure-openai-sdk-hackathon

Install the OpenAI .NET client library with:

dotnet add package Azure.AI.OpenAI

Add using statements:

using OpenAI.Chat;
using Azure.AI.OpenAI;

Add your environmental variables

string endpoint = "<Add AOAI GPT Enpoint>";
string deploymentName = "<Add AOAI GPT Key>";
string openAiApiKey = "<Add AOAI GPT Deployment name>";

string searchEndpoint = "<Add Azure Search Enpoint>";
string searchIndex = "<Add Azure Search Key>";
string searchApiKey = "<Add Azure Search Index for eCommerce products>";

Create client with an API key.

Note

While this is not as secure as Microsoft Entra-based authentication, it's possible to authenticate using a client subscription key. Avoid authenticating with api keys on production environments.

AzureOpenAIClient azureClient = new(
    new Uri(endpoint),
    new ApiKeyCredential(openAiApiKey));
ChatClient chatClient = azureClient.GetChatClient(deploymentName);

Use your own data with Azure OpenAI

#pragma warning disable AOAI001

//Add chat completion options with data source 
ChatCompletionOptions options = new ChatCompletionOptions();
options.AddDataSource(new AzureSearchChatDataSource()
{
    Endpoint = new Uri(searchEndpoint),
    IndexName = searchIndex,
    Authentication = DataSourceAuthentication.FromApiKey(searchApiKey),
});

//Add system message and user question
List<ChatMessage> messages = new List<ChatMessage>();
messages.Add(ChatMessage.CreateSystemMessage("You are an AI assistant that helps people find product information."));
messages.Add(ChatMessage.CreateUserMessage("<Type your question here.>"));

ChatCompletion completion = chatClient.CompleteChat(messages, options);

Use the above code as an example and do all necessary changes to meet the success criteria. You should make your application acting like a chat bot by adding conversation history as context for the subsequent calls.

Success Criteria

  • Demonstrate that the user can ask questions on your own data within the application.
  • Demonstrate that you set the behavior of the bot as a product information application.
  • Demonstrate that you use the conversation history as context for the subsequent calls.
  • (Optional) Demonstrate that you can stream the response chat messages.
  • Explain to your coach the key differences between Azure OpenAI SDK and Inference SDK.
  • Discuss with your coach alternative ways authenticating with Azure AI services.

Learning Resources
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