Generate images using Azure AI with .NET
Get started with Semantic Kernel by creating a simple .NET 8 console chat application. The application will run locally and use the OpenAI dell-e-3
model to generate postal card and invite your friends for a hike! Follow these steps to provision Azure OpenAI and learn how to use Semantic Kernel.
Get started with the .NET Azure OpenAI SDK by creating a simple .NET 8 console chat application. The application will run locally and use the OpenAI dell-e-3
model to generate postal card and invite your friends for a hike! Follow these steps to provision Azure OpenAI and learn how to use the .NET Azure OpenAI SDK.
Prerequisites
- .NET 8.0 SDK - Install the .NET 8.0 SDK
- An Azure subscription - Create one for free
- Azure Developer CLI - Install or update the Azure Developer CLI
- Access to Azure OpenAI service.
- On Windows, PowerShell
v7+
is required. To validate your version, runpwsh
in a terminal. It should returns the current version. If it returns an error, execute the following command:dotnet tool update --global PowerShell
.
Deploy the Azure resources
Ensure that you follow the Prerequisites to have access to Azure OpenAI Service as well as the Azure Developer CLI, and then follow the following guide to set started with the sample application.
Clone the repository: dotnet/ai-samples
From a terminal or command prompt, navigate to the quickstarts directory.
This provisions the Azure OpenAI resources. It may take several minutes to create the Azure OpenAI service and deploy the model.
azd up
Note
If you already have an Azure OpenAI service available, you can skip the deployment and use that value in the Program.cs, preferably from an IConfiguration
.
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.
Trying Generate Hiking Images sample
- From a terminal or command prompt, navigate to the
semantic-kernel\05-HikeImages
directory.
- From a terminal or command prompt, navigate to the
azure-openai-sdk\05-HikeImages
directory.
It's now time to try the console application. Type in the following to run the app:
dotnet run
If you get an error message the Azure OpenAI resources may not have finished deploying. Wait a couple of minutes and try again.
Understanding the code
Our application uses the Microsoft.SemanticKernel
package, which is available on NuGet, to send and receive requests to an Azure OpenAI service deployed in Azure.
The entire application is contained within the Program.cs file. 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();
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 AzureOpenAITextToImageService
service facilitates the requests and responses.
AzureOpenAITextToImageService textToImageService = new(deployment, endpoint, key, null);
Once the textToImageService
service is created, we we provide more context to the model by adding a system prompt. A good prompt to generate images requires a clear description: what is in the images, specific color to use, style (drawing, painting, realistic or cartoony). The model will use this prompt to generate the image. To have the model generate a response based off the user request, use the GenerateImageAsync
function, and specify the size and quality.
// Generate the image
string imageUrl = await textToImageService.GenerateImageAsync("""
A postal card with an happy hiker waving and a beautiful mountain in the background.
There is a trail visible in the foreground.
The postal card has text in red saying: 'You are invited for a hike!'
""", 1024, 1024);
Console.WriteLine($"The generated image is ready at:\n{imageUrl}");
Customize the prompt to personalize the images generated by the model.
Understanding the code
Our application uses the Azure.AI.OpenAI
client SDK, which is available on NuGet, to send and receive requests to an Azure OpenAI service deployed in Azure.
The entire application is contained within the Program.cs file. 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 openAIEndpoint = config["AZURE_OPENAI_ENDPOINT"];
string openAIDeploymentName = config["AZURE_OPENAI_GPT_NAME"];
string openAiKey = config["AZURE_OPENAI_KEY"];
// == Creating the AIClient ==========
var endpoint = new Uri(openAIEndpoint);
var credentials = new AzureKeyCredential(openAiKey);
The OpenAIClient
class facilitates the requests and responses. ChatCompletionOptions
specifies parameters of how the model will respond.
var openAIClient = new OpenAIClient(endpoint, credentials);
var completionOptions = new ChatCompletionsOptions
{
MaxTokens = 400,
Temperature = 1f,
FrequencyPenalty = 0.0f,
PresencePenalty = 0.0f,
NucleusSamplingFactor = 0.95f, // Top P
DeploymentName = openAIDeploymentName
};
Once the OpenAIClient
client is created, we we provide more context to the model by adding a system prompt. A good prompt to generate images requires a clear description: what is in the images, specific color to use, style (drawing, painting, realistic or cartoony). The model will use this prompt to generate the image.
string imagePrompt = """
A postal card with an happy hiker waving, there a beautiful mountain in the background.
There is a trail visible in the foreground.
The postal card has text in red saying: 'You are invited for a hike!'
""";
To have the model generate a response based off the user request, use the GetImageGenerationsAsync
function, and specify the size and quality.
Response<ImageGenerations> response = await openAIClient.GetImageGenerationsAsync(
new ImageGenerationOptions()
{
DeploymentName = openAIDalleName,
Prompt = imagePrompt,
Size = ImageSize.Size1024x1024,
Quality = ImageGenerationQuality.Standard
});
ImageGenerationData generatedImage = response.Value.Data[0];
if (!string.IsNullOrEmpty(generatedImage.RevisedPrompt))
{
Console.WriteLine($"\n\nInput prompt automatically revised to:\n {generatedImage.RevisedPrompt}");
}
Console.WriteLine($"\n\nThe generated image is ready at:\n {generatedImage.Url.AbsoluteUri}");
Customize the prompt to personalize the images generated by the model.
Clean up resources
When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
azd down
Next steps
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