Classify.ai is an AI-powered solution built to streamline and automate the classification of government documents. The application is built using Next.js for the frontend, integrated with Clerk for authentication, and leverages emailJS for communication. This repository contains the source code for the frontend, backend integration, and components required to classify documents with AI-driven text processing.
- AI-Powered Text Classification: Classify documents efficiently using our AI engine.
- User Authentication: Secure authentication for professionals and students using Clerk.
- Role-Based Access Control: Users are categorized into
professional
andstudent
roles for appropriate access. - Contact Form Integration: Users can send inquiries via the integrated email system (emailJS).
- Responsive Design: Modern, responsive UI with interactive elements and smooth animations.
Before running the project, ensure you have the following installed:
- Node.js (version 18+)
- npm or yarn
- A valid Clerk account for authentication
- EmailJS account for handling contact form submissions
- Clone the repository:
- Install dependencies:
- Set up your environment variables:
git clone https://github.com/yourusername/classify-ai.git
cd classify-ai
npm install
# or
yarn install
Create a .env.local
file at the root of your project and add the following:
NEXT_PUBLIC_CLERK_FRONTEND_API_KEY=your_clerk_frontend_key
NEXT_PUBLIC_EMAILJS_SERVICE_KEY=your_emailjs_service_key
NEXT_PUBLIC_EMAILJS_TEMPLATE_ID=your_template_id
NEXT_PUBLIC_EMAILJS_PUBLIC_KEY=your_public_key
After setting up your environment variables and installing dependencies, start the development server:
npm run dev
# or
yarn dev
Visit http://localhost:3000 to view the application in your browser.
This project uses Clerk for user authentication. Ensure you have a Clerk account and have set the appropriate API keys in the .env.local
file.
/api/classify
: Classifies text input based on predefined categories./api/contact
: Sends a message to the team using emailJS.
This project is licensed under the MIT License. See the LICENSE file for more details.