Junaid.GoogleGemini.Net 1.0.2

Junaid.GoogleGemini.Net

An open-source .NET library to use Gemini API based on Google�s largest and most capable AI model yet.

Installation

.NET CLI:

> dotnet add package Junaid.GoogleGemini.Net

Package Manager:

PM > Install-Package Junaid.GoogleGemini.Net

Usage

Authentication

Get an API key from Google's AI Studio here. Use GeminiConfiguration.ApiKey property to set the secret key.

GeminiConfiguration.ApiKey = "xxxxxxxxxxxxxxxxx";

TextService

TextService is used to generate text-only content. The GenereateContentAsync method takes a string (text prompt) as an argument and returns the textual data.

var service = new TextService();
var result = await service.GenereateContentAsync("Say Hi to me!");

VisionService

VisionService is used to generate content with both text and image inputs. The GenereateContentAsync method takes a string (text prompt) and FileObject (file bytes and file name) as an argument and returns the textual data.

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 Junaid.GoogleGemini.Net.Models.Requests.FileObject(fileBytes, fileName));

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.

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);

Contributing

Feel free to improve the library by adding new functionality, removing outdated functionality, updating broken functionality and refactoring code by using better Software Engineering practices, styles and patterns.

Getting Started

1. Start by forking the repository.
2. Clone the forked repository.
3. Create a new branch for your contribution.

Contribution Guidelines

• Adhere to the established code style within the project.
• Use meaningful commit messages.
• Please test your code and document the changes before creating a pull request.
• Push your changes to your fork and initiate a pull request against the master branch.
• Ensure your changes do not break existing functionality.
• While creating issues include detailed information, steps to reproduce the issue and check for existing issues to avoid duplicates.

Feel free to open an issue or contact me if you have any questions or suggestions.