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Summarize text using AI chat app with .NET

  • Artikkeli

Get started with AI by creating a simple .NET 8.0 console chat application to summarize text. The application runs locally and uses the OpenAI gpt-3.5-turbo model. Follow these steps to get access to OpenAI and learn how to use Semantic Kernel.

Prerequisites

  • .NET 8.0 SDK - Install the .NET 8.0 SDK.
  • An API key from OpenAI so you can run this sample.
  • On Windows, PowerShell v7+ is required. To validate your version, run pwsh in a terminal. It should return the current version. If it returns an error, execute the following command: dotnet tool update --global PowerShell.

Get started with AI by creating a simple .NET 8.0 console chat application to summarize text. The app runs locally and connects to the OpenAI gpt-35-turbo model deployed into Azure OpenAI. Follow these steps to provision the Azure OpenAI service and learn how to use Semantic Kernel.

Prerequisites

Get the sample project

Clone the GitHub repository that contains the sample apps for all of the quickstarts:

git clone https://github.com/dotnet/ai-samples.git

Create the Azure OpenAI service

The sample GitHub repository is structured as an Azure Developer CLI (azd) template, which azd can use to provision the Azure OpenAI service and model for you.

  1. From a terminal or command prompt, navigate to the src\quickstarts\azure-openai directory of the sample repo.

  2. Run the azd up command to provision the Azure OpenAI resources. It might take several minutes to create the Azure OpenAI service and deploy the model.

    azd up

    azd also configures the required user secrets for the sample app, such as the OpenAI access key.

    Note

    If you encounter an error during the azd up deployment, visit the troubleshooting section.

Try the hiking benefits sample

  1. From a terminal or command prompt, navigate to the openai\01-HikeBenefitsSummary directory.

  2. Run the following commands to configure your OpenAI API key as a secret for the sample app:

    dotnet user-secrets init
dotnet user-secrets set OpenAIKey <your-openai-key>

  3. Use the dotnet run command to run the app:

    dotnet run

  1. From a terminal or command prompt, navigate to the azure-openai\01-HikeBenefitsSummary directory.

  2. Use the dotnet run command to run the app:

    dotnet run

    Tip

    If you get an error message, the Azure OpenAI resources may not have finished deploying. Wait a couple of minutes and try again.

Explore the code

The app uses the Microsoft.SemanticKernel package to send and receive requests to the OpenAI service.

The Program.cs file contains all of the app code. The first several lines of code set configuration values and get the OpenAI Key that was previously set using the dotnet user-secrets command.

var config = new ConfigurationBuilder().AddUserSecrets<Program>().Build();
string model = "gpt-3.5-turbo";
string key = config["OpenAIKey"];

The Kernel class facilitates the requests and responses and registers an OpenAIChatCompletion service.

// Create a Kernel containing the OpenAI Chat Completion Service
Kernel kernel = Kernel.CreateBuilder()
    .AddOpenAIChatCompletion(model, key)
    .Build();

The application uses the Microsoft.SemanticKernel package to send and receive requests to the Azure OpenAI service.

The Program.cs file contains all of the app code. The first several lines of code load secrets and configuration values that were set in the dotnet user-secrets for you during the application provisioning.

// 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"];
string key = config["AZURE_OPENAI_KEY"];

The Kernel class facilitates the requests and responses and registers an OpenAIChatCompletion service.

// Create a Kernel containing the Azure OpenAI Chat Completion Service
Kernel kernel = Kernel.CreateBuilder()
    .AddAzureOpenAIChatCompletion(deployment, endpoint, key)
    .Build();

Once the Kernel is created, the app code reads the benefits.md file content and uses it to create a prompt for model. The prompt instructs the model to summarize the file text content.

// Create and print out the prompt
string prompt = $"""
    Please summarize the the following text in 20 words or less:
    {File.ReadAllText("benefits.md")}
    """;
Console.WriteLine($"user >>> {prompt}");

The InvokePromptAsync function sends the prompt to the model to generate a response.

// Submit the prompt and print out the response
string response = await kernel.InvokePromptAsync<string>(
    prompt,
    new(new OpenAIPromptExecutionSettings() 
        { 
            MaxTokens = 400 
        })
    );
Console.WriteLine($"assistant >>> {response}");

Customize the text content of the file or the length of the summary to see the differences in the responses.

Clean up resources

When you no longer need the sample application or resources, remove the corresponding deployment and all resources.

azd down

Troubleshoot

On Windows, you might get the following error messages after running azd up:

postprovision.ps1 is not digitally signed. The script will not execute on the system

The script postprovision.ps1 is executed to set the .NET user secrets used in the application. To avoid this error, run the following PowerShell command:

Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass

Then re-run the azd up command.

Another possible error:

'pwsh' is not recognized as an internal or external command, operable program or batch file. WARNING: 'postprovision' hook failed with exit code: '1', Path: '.\infra\post-script\postprovision.ps1'. : exit code: 1 Execution will continue since ContinueOnError has been set to true.

The script postprovision.ps1 is executed to set the .NET user secrets used in the application. To avoid this error, manually run the script using the following PowerShell command:

.\infra\post-script\postprovision.ps1

The .NET AI apps now have the user secrets configured and they can be tested.

Next steps