Build an AI powered twitter Bio Generator Using Next.js | Groq | Shadcn | Llama 3

Introduction

In recent months, the rise of generative AI has been hard to overlook, with many exciting applications emerging within this fascinating field. One of the most practical uses of generative AI is text generation. In this article, we will explore how to build an AI-powered Twitter bio generator using technologies like Next.js, Groq, Shadcn, Llama 3, and the Vercel AI SDK. By the end of this tutorial, you will have a comprehensive understanding of how to utilize generative AI for various projects.

Overview of the Generator

This bio generator application will consist of two main components: a configuration panel and an output display.

Configuration Panel: On the left-hand side, users can input personal information such as their profession, interests, and tone preferences while selecting the model and creativity settings. Users will also choose between a personal or brand bio.
Output Display: On the right-hand side, generated bios will be presented, showing results in real-time based on the user inputs.

Setting Up the Project

To get started, create a Next.js project. Use the following command in your terminal:

npx create-next-app@latest AI-powered-twitter-bio-generator --typescript --eslint --tailwindcss --src-dir --app-router

Once your project is set up, initialize Shadcn UI components. Visit the documentation and install the necessary dependencies using:

npx shadcn-ui@latest add

For our AI aspect, we’ll need to install the Vercel AI SDK, which offers an interface for using models like Llama 3 without incurring any costs.

Designing the UI

After setting up the dependencies, use components from both Shadcn UI and Magic UI for design aesthetics. The components will include buttons, sliders, forms, and text areas.

Home Layout

In your pages/index.tsx, remove the boilerplate code and replace it with a custom design. Use Tailwind CSS classes for styling to improve responsiveness.

User Input Form

Create a component for user input with form validation using Zod to manage user inputs. The form should include the following fields:

Model Selection
Creativity Slider
User Information Text Area
Type (Personal/Brand)
Tone (Funny/Professional/Etc.)
Emoji Toggle

Output Component

The output component should render the generated bios upon submission. Use hooks to manage loading states and display the generated bios.

Integrating AI Models

For the AI integration, use Groq to set up a server action that handles the functioning of generating bios. The generateBio function will accept user input and provide a response from the selected model.

Context API for State Management

Using Context API, you can manage output states across components. Create a BioContext.tsx file to provide global states such as output and loading.

Adding Copy Feature

Include a copy feature to allow users to easily copy their favorite bio. Create a CopyLabel.tsx component that updates the label when the bio is copied to the clipboard.

Final Touches and Responsiveness

Adjust padding and layout for mobile responsiveness using Tailwind CSS. Ensure the application looks great on both desktop and mobile platforms.

Conclusion

After following this tutorial, you should have a fully functional AI-powered Twitter bio generator. You now understand how to integrate generative AI models within a Next.js application! If you are interested in exploring more generative AI applications or have particular project ideas, share them in the comments. Don’t forget to like, share, and subscribe!

Keywords

Generative AI
Twitter Bio Generator
Next.js
Groq
Shadcn
Llama 3
Vercel AI SDK
Responsive Design
State Management

FAQ

Q1: What technologies are used in the Twitter Bio Generator?
A1: The project utilizes Next.js for the framework, Groq for AI model management, Shadcn for UI components, Llama 3 as the AI model, and the Vercel AI SDK for seamless integration.

Q2: Can I customize the tone and type of bios generated?
A2: Yes, users can select the tone (funny, professional, etc.) and type (personal or brand) to customize the bios generated.

Q3: Is the application mobile responsive?
A3: Yes, the application is designed with Tailwind CSS to ensure a responsive layout, making it user-friendly on both desktop and mobile devices.

Q4: How does the application handle user input validation?
A4: The application uses Zod for schema validation to ensure all user inputs meet the required criteria before processing them.

Q5: What is the purpose of the copy feature in the application?
A5: The copy feature allows users to easily copy the generated bios to their clipboard for quick use on Twitter or other platforms.

Build an AI powered twitter Bio Generator Using Next.js | Groq | Shadcn | Llama 3 | Vercel AI SDK