Welcome to DotnetGeminiSDK, a .NET SDK for interacting with the Google Gemini API. This SDK empowers developers to harness the capabilities of machine learning models to generate creative content effortlessly.
Google Gemini is an advanced AI platform that offers various interfaces for commands tailored to different use cases. It allows users to interact with machine learning models for generating content and responses to instructions. The platform supports free-form commands, structured commands, and chat-based requests. Additionally, Gemini provides the ability to adjust models for specific tasks, enhancing their performance for particular use cases.
Get started by installing the DotnetGeminiSDK NuGet package. Run the following command in the NuGet Package Manager Console:
Install-Package DotnetGeminiSDKOr, if you prefer using the .NET CLI:
dotnet add package DotnetGeminiSDKTo use the Gemini SDK, configure the GoogleGeminiConfig object. Add the Gemini client to your service collection using GeminiServiceExtensions:
Note
Only used when using the dependency injection method.
using DotnetGeminiSDK;
using Microsoft.Extensions.DependencyInjection;
public class Startup
{
public void ConfigureServices(IServiceCollection services)
{
services.AddGeminiClient(config =>
{
config.ApiKey = "YOUR_GOOGLE_GEMINI_API_KEY";
config.ImageBaseUrl = "CURRENTLY_IMAGE_BASE_URL";
config.TextBaseUrl = "CURRENTLY_IMAGE_BASE_URL";
});
}
}When you incorporate the Gemini client, you can seamlessly inject it into your code for immediate use.
using DotnetGeminiSDK.Client.Interfaces;
using Microsoft.Extensions.DependencyInjection;
public class YourClass
{
private readonly IGeminiClient _geminiClient;
public YourClass(IGeminiClient geminiClient)
{
_geminiClient = geminiClient;
}
public async Task Example()
{
var response = await _geminiClient.TextPrompt("Text for processing");
// Process the response as needed
}
}If you don't want to use dependency injection, you can instantiate the GeminiClient class, as a constructor parameter, place your settings in the GoogleGeminiConfig instance.
using DotnetGeminiSDK.Client.Interfaces;
public class YourClass
{
private readonly GeminiClient _geminiClient;
public YourClass()
{
_geminiClient = new GeminiClient(new GoogleGeminiConfig(){ //Place your settings here });
}
public async Task Example()
{
var response = await _geminiClient.TextPrompt("Text for processing");
// Process the response as needed
}
}- Text Prompt
- Stream Text Prompt
- Multiple Text Prompt
- Image Prompt
- Counting Tokens
- Get Model
- List Models
- Embedding
- Batch Embedding
Prompt the Gemini API with a text message using the TextPrompt method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.TextPrompt("Write a story about a magic backpack");Prompt the Gemini API with a text message using the StreamTextPrompt method:
Note
This diffears from the text prompt, it receives the response as string and in chunks.
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.StreamTextPrompt("Write a story about a magic backpack", (chunk) => {
Console.WriteLine("Process your chunk of response here");
});Prompt the Gemini API with multiple text messages using the TextPrompt method with a list of Content objects:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var messages = new List<Content>
{
new Content
{
Parts = new List<Part>
{
new Part
{
Text = "Write a story about a magic backpack"
}
}
},
// Add more Content objects as needed
};
var response = await geminiClient.TextPrompt(messages);Get the specific model details of Gemini using GetModel method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.GetModel("gemini-model-v1");Get all Gemini models using GetModels method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.GetModels();Prompt the Gemini API with a text message using the CountTokens method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.CountTokens("Write a story about a magic backpack");Note
You can use list of messages and list of content to call this method too.
Prompt the Gemini API with an image and a text message using the ImagePrompt method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var image = File.ReadAllBytes("path/to/your/image.jpg");
var response = await geminiClient.ImagePrompt("Describe this image", image, ImageMimeType.Jpeg);Prompt the Gemini API with an base64 string and a text message using the ImagePrompt method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var base64Image = "image-as-base64";
var response = await geminiClient.ImagePrompt("Describe this image in details", base64Image, ImageMimeType.Jpeg);Prompt the Gemini API with a text message and using embedded technique using the EmbeddedContentsPrompt method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.EmbeddedContentsPrompt("Write a story about a magic backpack");Note
You can use list of messages and list of content to call this method too.
Prompt the Gemini API with a text message and using batch embedded technique using the BatchEmbeddedContentsPrompt method:
var geminiClient = serviceProvider.GetRequiredService<IGeminiClient>();
var response = await geminiClient.EmbeddedContentsPrompt("Write a story about a magic backpack");Note
You can use list of messages and list of content to call this method too.
Contributions are welcome! Feel free to open issues or pull requests to enhance the SDK.
This project is licensed under the MIT License.