Junaid.GoogleGemini.Net
3.1.1
See the version list below for details.
dotnet add package Junaid.GoogleGemini.Net --version 3.1.1
NuGet\Install-Package Junaid.GoogleGemini.Net -Version 3.1.1
<PackageReference Include="Junaid.GoogleGemini.Net" Version="3.1.1" />
paket add Junaid.GoogleGemini.Net --version 3.1.1
#r "nuget: Junaid.GoogleGemini.Net, 3.1.1"
// Install Junaid.GoogleGemini.Net as a Cake Addin #addin nuget:?package=Junaid.GoogleGemini.Net&version=3.1.1 // Install Junaid.GoogleGemini.Net as a Cake Tool #tool nuget:?package=Junaid.GoogleGemini.Net&version=3.1.1
Junaid.GoogleGemini.Net
An open-source .NET library to use Gemini API based on Google�s largest and most capable AI model yet.
Installation of Nuget Package
.NET CLI:
> dotnet add package Junaid.GoogleGemini.Net
Package Manager:
PM > Install-Package Junaid.GoogleGemini.Net
Authentication
Get an API key from Google's AI Studio here.
Either of the following three ways can be used to set the API key:
Use the
GeminiConfiguration.ApiKey
property to set the secret API key directly in your application code.GeminiConfiguration.ApiKey = "xxxxxxxxxxxxxxxxx";
Or pass the API key as an environment variable named "GeminiApiKey".
Or pass the API key as the "GeminiApiKey" field inside an
App.config
file.<?xml version="1.0" encoding="utf-8" ?> <configuration> <appSettings> <add key="GeminiApiKey" value="xxxxxxxxxxxxxxxxx" /> </appSettings> </configuration>
Services
There are three services named TextService
, VisionService
and ChatService
. All of the services contain the GenereateContentAsync
method to generate text-only content, the StreamGenereateContentAsync
method to provide a stream of text-only output and the CountTokensAsync
method to count tokens.
GenereateContentAsync
is used to generate content in textual form. The input parameters to this method vary from service to service, however, an optional input parameter named configuration
of type GenerateContentConfiguration
is common among all services. For information on its usage navigate to the configuration section of this page.
The GenereateContentAsync
method returns the GenerateContentResponse
object. To just get the text string inside this object, use the method Text()
as shown in the code snippets given below.
The StreamGenereateContentAsync
takes the same parameters as GenereateContentAsync
in their respective service, with an additional delegate Action<string>
.
The CountTokensAsync
method takes the same parameters as GenereateContentAsync
in their respective service. It does not take the optional configuration
parameter.
There are two ways of initializing a service instance. Either create an instance with the default constructor or pass in a custom GeminiClient
object to the parameterized constructor. For information on GeminiClient
and its usage navigate to the GeminiClient section of this page.
The following sections show example code snippets that highlight how to use these services.
TextService
TextService
is used to generate content with text-only input.
The GenereateContentAsync
method takes a mandatory string
(text prompt) as input, an optional GenerateContentConfiguration
(model parameters and safety settings) argument and returns the GenerateContentResponse
response object.
var service = new TextService();
var result = await service.GenereateContentAsync("Say Hi to me!");
Console.WriteLine(result.Text());
The StreamGenereateContentAsync
method is used to generate the stream of text-only content.
var service = new TextService();
Action<string> handleStreamData = (data) =>
{
Console.WriteLine(data);
};
await service.StreamGenereateContentAsync("Write a story on Google AI.", handleStreamData);
The CountTokensAsync
method is used to get the total tokens count. When using long prompts, it might be useful to count tokens before sending any content to the model.
var service = new TextService();
var result = await service.CountTokensAsync("Write a story on Google AI.");
Console.WriteLine(result.totalTokens);
VisionService
VisionService
is used to generate content with both text and image inputs.
The GenereateContentAsync
method takes mandatory string
(text prompt) and FileObject
(file bytes and file name), an optional GenerateContentConfiguration
(model parameters and safety settings) argument and returns the GenerateContentResponse
response object.
string filePath = "path/<imageName.imageExtension>";
var fileName = Path.GetFileName(filePath);
byte[] fileBytes = Array.Empty<byte>();
try
{
using (var imageStream = new FileStream(filePath, FileMode.Open, FileAccess.Read))
using (var memoryStream = new MemoryStream())
{
imageStream.CopyTo(memoryStream);
fileBytes = memoryStream.ToArray();
}
Console.WriteLine($"Image loaded successfully. Byte array length: {fileBytes.Length}");
}
catch (Exception ex)
{
Console.WriteLine($"Error: {ex.Message}");
}
var service = new VisionService();
var result = await service.GenereateContentAsync("Explain this image?", new FileObject(fileBytes, fileName));
Console.WriteLine(result.Text());
The StreamGenereateContentAsync
method is used to generate the stream of text-only content.
......
var service = new VisionService();
Action<string> handleStreamData = (data) =>
{
Console.WriteLine(data);
};
await service.StreamGenereateContentAsync("Explain this image?", new FileObject(fileBytes, fileName), handleStreamData);
The CountTokensAsync
method is used to get the total tokens count. When using long prompts, it might be useful to count tokens before sending any content to the model.
......
var service = new VisionService();
var result = await service.CountTokensAsync("Explain this image?", new FileObject(fileBytes, fileName));
Console.WriteLine(result.totalTokens);
ChatService
ChatService
is used to generate freeform conversations across multiple turns with chat history as input.
The GenereateContentAsync
method takes an array of MessageObject
as an argument, an optional GenerateContentConfiguration
(model parameters and safety settings) argument and returns the GenerateContentResponse
response object.
Each MessageObject
contains two fields i.e. a string
named role (value can be either of "model" or "user" only) and another string
named text (text prompt).
var chat = new MessageObject[]
{
new MessageObject( "user", "Write the first line of a story about a magic backpack." ),
new MessageObject( "model", "In the bustling city of Meadow brook, lived a young girl named Sophie. She was a bright and curious soul with an imaginative mind." ),
new MessageObject( "user", "Write one more line." ),
};
var service = new ChatService();
var result = await service.GenereateContentAsync(chat);
Console.WriteLine(result.Text());
The StreamGenereateContentAsync
method is used to generate the stream of text-only content.
......
var service = new ChatService();
Action<string> handleStreamData = (data) =>
{
Console.WriteLine(data);
};
await service.StreamGenereateContentAsync(chat, handleStreamData);
The CountTokensAsync
method is used to get the total tokens count. When using long prompts, it might be useful to count tokens before sending any content to the model.
......
var service = new ChatService();
var result = await service.CountTokensAsync(chat);
Console.WriteLine(result.totalTokens);
Configuration
Configuration input can be used to control the content generation by configuring model parameters and by using safety settings.
An example of setting the configuration
parameter of type GenerateContentConfiguration
and passing it to the GenereateContentAsync
method of TextService
is as follows:
var configuration = new GenerateContentConfiguration
{
safetySettings = new []
{
new SafetySetting
{
category = CategoryConstants.DangerousContent,
threshold = ThresholdConstants.BlockOnlyHigh
}
},
generationConfig = new GenerationConfig
{
stopSequences = new List<string> { "Title" },
temperature = 1.0,
maxOutputTokens = 800,
topP = 0.8,
topK = 10
}
};
var service = new TextService();
var result = await service.GenereateContentAsync("Write a quote by Aristotle.", configuration);
Console.WriteLine(result.Text());
GeminiClient
GeminiClient
contains the ApiKey
and HttpClient
objects. The default instance of GeminiClient
is automatically created with the initialization of the service object. However, a case may arise where a custom GeminiClient
is needed.
For example: Using proxy
In such a scenario, a custom HttpClient
object will be used to set proxy parameters. This object will then be used to initialize the GeminiClient
.
using HttpClientHandler httpClientHandler = new HttpClientHandler()
{
Proxy = new WebProxy()
{
Address = new Uri("xxxxxxxxxxxx"),
},
UseProxy = true,
};
using HttpClient httpClient = new HttpClient(httpClientHandler, false);
httpClient.BaseAddress = new Uri("https://generativelanguage.googleapis.com");
httpClient.DefaultRequestHeaders.Add("X-Goog-Api-Key", "xxxxxxxxxxxx");
GeminiConfiguration.GeminiClient = new GeminiClient(httpClient);
In the above example, the GeminiClient
instance is assigned to the static GeminiClient
property of the GeminiConfiguration
object. This can then be used with all instances of the different services.
......
GeminiConfiguration.GeminiClient = new GeminiClient(httpClient);
The GeminiClient
instance can also be set at the service level. With this different instances can be used with different services.
......
var textService = new TextService(new GeminiClient(httpClient));
var textServiceResult = await textService.GenereateContentAsync("Write a short poem on friendship.");
Thanks for using this library.
Contributions are welcome. Please read the contributing guidelines.
The API is being manually released on Nuget.org. The release notes file lists down the release notes.
Feel free to contact me via email if you have any questions or suggestions.
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net6.0 is compatible. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 is compatible. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
-
net6.0
- System.Configuration.ConfigurationManager (>= 6.0.0)
-
net7.0
- System.Configuration.ConfigurationManager (>= 6.0.0)
-
net8.0
- System.Configuration.ConfigurationManager (>= 6.0.0)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
Internal refactoring for the stream content method to reduce memory consumption and improving performance.