Quickstart: Use Gemini with .NET (Google AI)

This quickstart shows you how to get started with the Gemini API using an SDK for .NET called Mscc.GenerativeAI.

Prerequisites

To complete this quickstart locally, ensure that your .NET development meets the following requirements:

• .NET 6+ or
• .NET Framework 4.7.2+

The NuGet package also supports .NET Standard 2.0.

Set up your API key

To use the Gemini API, you'll need an API key. If you don't already have one, create a key in Google AI Studio.

In order to keep private, sensitive information and secrets out of your source code repositories, it is recommended to use either Environment Variables, User Secrets, or a Key/Secrets Manager to retrieve data like an API key. Here, I'm going to create an .env file and place it into the project folder with the following content.

GOOGLE_API_KEY=<The generated Gemini API key>

To access the value of a variable that is defined in a .env file, use $dotenv. More details are described under Environment Variables  in the official documentation.

Set the file properties with a Build action of None and copy instructions of Copy, if newer.

<None Update=".env" Condition="Exists('.env')">
    <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</None>

Install the SDK / NuGet package

The SDK for .NET for the Gemini API is contained in the Mscc.GenerativeAI package. Install the dependency using dotnet CLI:

dotnet add package Mscc.GenerativeAI

See README for alternative options, like the NuGet Package Manager.

Initialize the Generative Model

Before you can make any API calls, you need to add a reference to the namespace Mscc.GenerativeAI and initialize the Generative Model.

using Mscc.GenerativeAI;

var googleAI = new GoogleAI(apiKey: Environment.GetEnvironmentVariable("GOOGLE_API_KEY");
var model = googleAI.GenerativeModel(model: Model.GeminiPro);

Generate Text

var response = await model.GenerateContent("Write a story about a magic backpack.");
Console.WriteLine(response.Text);

What's next

Explore the README of the NuGet package which has more samples documented. All unit tests are accessible in the GitHub repository:

If you're new to generative AI models, you might want to look at the concepts guide and the Gemini API overview before trying a quickstart.