How to Use Google Gemini with Semantic Kernel

In the ever-evolving world of artificial intelligence, combining powerful tools can open up new avenues for innovation and efficiency. Today, we're diving into how to use Google Gemini with Semantic Kernel—a match made in AI heaven. Whether you're an AI enthusiast, developer, or data scientist, this guide will walk you through the integration process step-by-step, ensuring you harness the full potential of these technologies.

If you're more interested in watching the entire process, then here is the video:

What is Google Gemini?

Google Gemini is a suite of generative AI models designed to handle multiple types of data, including text, images, and audio. Its multimodal capabilities make it a versatile tool for a wide range of applications, from natural language processing to creative content generation.

Introduction to Semantic Kernel

Microsoft Semantic Kernel is an open-source development kit designed to help developers integrate AI models into their applications. It supports multiple programming languages, including C#, Python, and Java. By integrating Semantic Kernel with Google Gemini, you can leverage the strengths of both tools to achieve superior results.

Setting Up the Environment

Before we dive into the integration, let's set up the necessary environment

- Go to Google AI Studio and grab the model's name and an API key

- Install dependencies using Nuget Package Manager as this would be a C#.Net application: Microsoft.SemanticKernel and Microsoft.SemanticKernel.Connectors.Google

Integrating Google Gemini with Semantic Kernel

Once your environment is set up, you can start integrating Google Gemini with Semantic Kernel. 

using Microsoft.SemanticKernel;

using Microsoft.SemanticKernel.ChatCompletion;

#pragma warning disable SKEXP0070

var kernel = Kernel.CreateBuilder().AddGoogleAIGeminiChatCompletion("gemini-1.5-pro",Configuration.API_KEY).Build();

var chatService = kernel.GetRequiredService<IChatCompletionService>();

var history = new ChatHistory();

history.AddUserMessage("What is the color of the sky?");

var response = await chatService.GetChatMessageContentsAsync(history);

System.Console.WriteLine(response[0].Content);

Conclusion

Integrating Google Gemini with Semantic Kernel can significantly enhance your AI projects, offering a powerful combination of generative and analytical capabilities. By following the steps outlined in this guide, you'll be well on your way to unlocking new potentials in your AI applications. 

Happy coding!