Project-Lakshya is an intelligent, full-stack web application designed to help students discover their ideal career path through personalized assessments and AI-driven recommendations.

• Comprehensive Assessments: Multi-phase quizzes covering personality traits, physical appearance, and academic interests.
• AI-Powered Predictions: Machine learning model to analyze results and recommend career fields.
• Dynamic User Profiles: User authentication and profile management to track academic details, interests, and goals.
• Smart Institution Search: Suggests colleges and auto-fills location data for faster profile setup.
• Interactive Dashboard: Central hub to view results, track progress, and access platform features.

• Personality & Trait Analysis → 50%
• Academic Interests → 30%
• Skill Evaluation → 20%

Create Profile→Take Assessments→ AI Analysis →View Results

Follow these steps to run Project-Lakshya locally.

Ensure you have installed:

• Git
• Node.js (v18.x or later) & npm
• Python (v3.9 or later) & pip

1. Clone the Repository

git clone https://github.com/AnshMNSoni/Project-Lakshya.git
cd Project-Lakshya

2. Frontend Setup

cd src   # Or your frontend source folder
npm install

• Create a .env file in src/ by copying from example:

cp .env.example .env

• Fill in:

VITE_SUPABASE_URL=your_supabase_url
VITE_SUPABASE_ANON_KEY=your_supabase_anon_key

3. Backend Setup

git clone https://github.com/AnshMNSoni/Project-Lakshya.git
cd Project-Lakshya

1. Start Backend Server

git clone https://github.com/AnshMNSoni/Project-Lakshya.git
cd Project-Lakshya

2. Start Frontend Development Server

git clone https://github.com/AnshMNSoni/Project-Lakshya.git
cd Project-Lakshya

3. Open in Browser

git clone https://github.com/AnshMNSoni/Project-Lakshya.git
cd Project-Lakshya

https://project-lakshya.lovable.app/

• login page

• Sign up page

• Sign in page

• Dashbord

• Quiz 1

• Quiz 2

• Quiz results

-recommended college on map

• Map view

• Info in map

• details of college

Contributions are welcome! 🎉

1. Fork the repo
2. Create your feature branch (git checkout -b feature/NewFeature)
3. Commit your changes (git commit -m 'Add some NewFeature')
4. Push to branch (git push origin feature/NewFeature)
5. Open a Pull Request

This project is licensed under the MIT License.
See the LICENSE file for details.

👤 Ansh Soni

• GitHub: AnshMNSoni
• Project Link: Project-Lakshya