🚀 AlgoGuide — Personalized Interview Preparation Platform

AlgoGuide is an adaptive interview preparation platform designed to replace static problem lists with a personalized, data-driven learning experience. The system analyzes user performance, tracks topic proficiency, and recommends relevant problems and learning resources to accelerate preparation.

Important

Backend Requirement: This repository contains the Frontend code only. The full system architecture includes a Node.js/Express backend and a Python AI service. Ensure these services are running for full functionality.

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📌 Motivation

Traditional interview preparation relies on fixed question sheets that do not adapt to individual strengths, weaknesses, or target roles. AlgoGuide creates a smarter workflow that evolves with the learner using performance analytics and AI-driven recommendations.

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🏗️ System Architecture

graph TD
    User([User])

    subgraph Frontend
        FrontendApp[React App]
    end

    subgraph Backend
        API[Express API]
        Auth[Auth Service]
    end

    subgraph AI_Layer
        AI[LLM Service - Python]
    end

    subgraph Database
        DB[(Firebase)]
    end

    User --> FrontendApp
    FrontendApp --> API
    API --> Auth
    API --> DB
    API --> AI
    AI --> DB

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🚀 Key Features

• 🧠 Personalized Learning Paths — Tailored based on user performance
• 📈 Readiness & Progress Scoring — Dynamic tracking of preparation
• 🎯 Adaptive Problem Recommendations — Smart next-question suggestions
• 🤖 AI-Powered Assistance — 24/7 doubt-solving mentor
• 🗣️ Mock Interviews — Real-time voice-based interviews
• 📊 Analytics Dashboard — Visual performance tracking
• 👨‍💻 Code Editor — Practice directly in browser

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📊 How It Works

1. User defines preparation goals
2. Platform tracks topic-wise performance
3. Recommendation engine suggests next problems
4. AI assistant provides guidance
5. Readiness score updates dynamically

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🔥 Core Concepts

• Adaptive Recommendation Systems
• Scalable Backend API Design
• Data-Driven Personalization
• AI-Assisted Workflows
• System Design Architecture

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⚙️ Technology Stack

Frontend

• React + Vite
• Tailwind CSS
• Clerk Authentication

Backend

• Node.js
• Express.js
• Firebase (Firestore + Auth)

AI & Analytics

• Python (LLM Integration)
• Voice AI: Vapi, Deepgram, ElevenLabs
• Performance Scoring Algorithms

Tools

• Git
• VS Code
• Postman

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🧩 Personal Contribution

• Designed full system architecture
• Built backend APIs (Node.js/Express)
• Integrated Firebase authentication and database
• Implemented AI-powered interview and recommendation system

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🚧 Future Improvements

• Microservices architecture (Spring Boot)
• Advanced ML-based recommendation engine
• Enhanced analytics and insights

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📋 Prerequisites

Make sure you have:

• Node.js (v18+)
• npm or yarn

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⚙️ Installation

1. Clone Repository

git clone https://github.com/yourusername/AlgoGuide-Frontend.git
cd AlgoGuide-Frontend/AlgoGuide

2. Install Dependencies

npm install

3. Setup Environment Variables

Create a .env file:

VITE_CLERK_PUBLISHABLE_KEY=your_clerk_key
VITE_FIREBASE_API_KEY=your_firebase_key
VITE_FIREBASE_AUTH_DOMAIN=your_project.firebaseapp.com
VITE_FIREBASE_PROJECT_ID=your_project_id
VITE_FIREBASE_STORAGE_BUCKET=your_project.appspot.com
VITE_FIREBASE_MESSAGING_SENDER_ID=your_sender_id
VITE_FIREBASE_APP_ID=your_app_id
VITE_FIREBASE_MEASUREMENT_ID=your_measurement_id
GEMINI_API_KEY=your_gemini_key

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🏃‍♂️ Running the App

npm run dev

App runs at:

http://localhost:5173

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📂 Project Structure

src/
├── components/
│   ├── roadmap/
│   ├── Hero.jsx
│   └── ...
├── pages/
│   ├── Dashboard.jsx
│   ├── Landing.jsx
│   ├── Onboarding.jsx
│   ├── SignIn.jsx
│   └── ...
├── SDEInterview.jsx
├── App.jsx
└── main.jsx

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🤝 Contributing

1. Fork the repo

2. Create a branch

   git checkout -b feature/your-feature

3. Commit changes

4. Push to GitHub

5. Create Pull Request

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📄 License

This project is licensed under the MIT License.

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⭐ Final Note

AlgoGuide is not just a project — it's a complete system design + AI application showcasing:

• Full-stack engineering
• AI integration
• Scalable architecture

Perfect for placements, internships, and portfolio 🚀