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How to Use Gemini API in NextJs
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Tech Wizard✨Author
Jul 30, 2024
4 min read

How to Use Gemini API in NextJs

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AI apps are evolving rapidly, which is great news for developers and users. I'm interested in using AI to generate blog article summaries to make it easier for readers to grasp the main points before diving into the full article.

This article discusses the process of integrating the Gemini API in NextJS and the various functionalities it offers. You'll be surprised to learn how straightforward incorporating the API into your app is. Before I begin, I'd like to shout out to Avinash Prasad for providing a simple guide."

Step 1: Obtain the Gemini API Key

To begin, head over to Google AI Studio and create a free GEMINI API Key. This key will enable you to communicate with various Gemini Models. Save the key in .env file as GEMINI_API_KEY.

Step 2: Install Google Generative AI Package

Install the Google AI JavaScript SDK enables you to use Google’s generative AI models. Make sure you are in your project’s root directory and run the following command in your terminal:

Step 3: Create An API Route to Handle Requests

In the API folder, create a router handle that helps you communicate with Gemini. For this tutorial, I named the file Gemini and added a route.ts file. Requests to Gemini will go to /API/Gemini

Step 4: Create A Helper Function

Since this is a post route, we need a function that receives the message body and fetches data from this route. I recommend creating a function in a lib file for reusability and type safety.

Step 4: Fetching Data

We can now import this function and call it whenever we need to contact Gemini by passing the message prop.

This simple code uses server actions to send the message. However, we need to handle what to do with the data and might need to useState to store the response we get from the handleGenerate

Step 5: Rendering Data

Advanced 

Depending on your use case, you might need to stream the incoming data to the client. For example, if you are creating a chatbot. You can stream the data by using Gemini in combination with FastAPI to return chucks:

Conclusion

Integrating the Gemini model into your app is as simple as adding the above code block. However, note there are rate limitations and you might need to modify your model to limit the tokens utilized per each response.

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