📚 StudyFlux – Personalized AI Learning Platform

▶ Live Demo: study-flux.vercel.app

Contributors

• N1KH1LT0X1N
• vi800
• AstralKS
• MalayBhaveshPandya

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StudyFlux is a highly personalized AI-powered learning platform designed to make studying more interactive, engaging, and effective. With unique contextualization per user, multilingual support, flashcards, live Q&A, personalized dashboards, and leaderboards, StudyFlux adapts to each learner’s journey.

Built with a scalable MERN + Next.js stack and powered by AI agents, StudyFlux ensures students never lose context across sessions.

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🚀 Key Features

• 🧠 Personalized AI Chatbot

  • Learns from user history & previous conversations.
  • Provides contextual answers based on past performance.

• 🌍 Multilingual Support

  • Chat, flashcards, and UI available in multiple languages.

• 📑 Flashcards + Adaptive Questions

  • AI-generated flashcards from uploaded content.
  • Spaced-repetition algorithm for effective memorization.

• 📊 Personalized Dashboard

  • Track learning progress, scores, and activity.
  • Compare performance via leaderboards.

• 📝 Conversation Summarization

  • Every interaction is summarized & stored for future sessions.
  • Keeps personalization alive long-term.

• 📂 File → Flashcards/Q&A Workflow

  • Upload files (Google Drive support).
  • AI extracts key concepts → flashcards + quiz-ready Q&A.

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⚙️ Technical Stack

Frontend (Student-facing)

• MERN + Next.js
• Next.js → SSR/SSG for SEO & performance.
• React → Interactive UI (flashcards, leaderboards, dashboards).
• UI Features → Personalized dashboards, multilingual toggle, live chat.

Backend (APIs + Business Logic)

• Node.js (Express) → API handling.
• AI Integration: Gemini 2.5 Pro → Core reasoning + conversation generation.
• Workflow Orchestration: n8n → Service automation & pipeline execution.

Data Layer

• MongoDB → Stores user profiles, scores, progress, conversation summaries.
• Pinecone (Vector DB) → Stores embeddings of conversations & files for semantic search.
• MongoDB Vector Search → Alternative for embeddings storage & quick retrieval.

AI Agents

1. Flashcard Agent → Adaptive flashcard generation (via Pinecone vector search).
2. Q&A Agent → Contextual answering, difficulty adapts to student’s profile.
3. Conversation Summarizer → Summarizes chats → stored in MongoDB.

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🔄 Workflow Example (File → Flashcards/Q&A)

1. Student uploads file (Google Drive).

2. n8n workflow triggers:

   • Extracts file → sends embeddings to Pinecone.
   • Metadata registered in MongoDB.

3. Flashcard Agent generates adaptive flashcards.

4. Q&A Agent fetches data from Pinecone + convo history → answers queries.

5. Conversation Summarizer logs structured summaries in MongoDB.

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🏗️ System Architecture

flowchart TD

A[Student Uploads File] -->|Google Drive| B[n8n Workflow]
B --> C[Pinecone: Embeddings Storage]
B --> D[MongoDB: Metadata + User Data]

C --> E[Flashcard Agent]
D --> E
C --> F[Q&A Agent]
D --> F
F --> D

E --> G[Frontend: Next.js Dashboard]
F --> G
D --> G

G -->|Chat/Flashcards/Leaderboard| A

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📂 Project Structure

StudyFlux/
└── ./
    ├── app
    │   ├── (auth)
    │   │   ├── reset-password
    │   │   │   └── page.tsx
    │   │   ├── signin
    │   │   │   └── page.tsx
    │   │   ├── signup
    │   │   │   └── page.tsx
    │   │   └── layout.tsx
    │   ├── (default)
    │   │   ├── layout.tsx
    │   │   └── page.tsx
    │   ├── api
    │   │   └── hello
    │   │       └── route.ts
    │   ├── css
    │   │   ├── additional-styles
    │   │   │   ├── theme.css
    │   │   │   └── utility-patterns.css
    │   │   └── style.css
    │   ├── dashboard
    │   │   ├── components
    │   │   │   ├── Chat.css
    │   │   │   ├── Chat.jsx
    │   │   │   ├── FileUpload.jsx
    │   │   │   ├── Header.jsx
    │   │   │   ├── Loader.css
    │   │   │   ├── Loader.jsx
    │   │   │   ├── Summary.css
    │   │   │   └── Summary.jsx
    │   │   ├── App.css
    │   │   ├── App.jsx
    │   │   ├── index.css
    │   │   └── page.tsx
    │   └── layout.tsx
    ├── components
    │   ├── ui
    │   │   ├── footer.tsx
    │   │   ├── header.tsx
    │   │   └── logo.tsx
    │   ├── cta.tsx
    │   ├── features.tsx
    │   ├── hero-home.tsx
    │   ├── modal-video.tsx
    │   ├── page-illustration.tsx
    │   ├── spotlight.tsx
    │   ├── testimonials.tsx
    │   └── workflows.tsx
    ├── public
    │   └── app.js
    ├── utils
    │   ├── useMasonry.tsx
    │   └── useMousePosition.tsx
    ├── next-env.d.ts
    ├── next.config.js
    └── postcss.config.js

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🛠️ Installation & Setup

Prerequisites

• Node.js >= 18
• MongoDB (local/Atlas)
• Pinecone account
• n8n (self-hosted / cloud)

Steps

# 1. Clone repository
git clone https://github.com/N1KH1LT0X1N/StudyFlux.git
cd StudyFlux

# 2. Install dependencies
npm install   # (or yarn / pnpm)

# 3. Setup environment variables
cp .env.example .env
# Add MongoDB, Pinecone, Gemini API keys

# 4. Run development servers
cd frontend && npm run dev   # Next.js frontend
cd backend && npm run dev    # Express backend

# 5. Start n8n workflows
n8n start

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📊 Example Use Cases

• Student Learning → Upload notes → get flashcards + quizzes.
• Competitive Exams → Multilingual flashcards + mock tests.
• Institution Deployment → Class leaderboards + progress tracking.

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🌱 Future Roadmap

• AI-powered Exam Mock Agent.
• Gamified learning streaks.
• Offline mode (PWA).
• Institution-specific integrations (LMS, ERP).
• Advanced analytics (weak topic detection).

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🤝 Contributing

We welcome contributions!

1. Fork the repo
2. Create a feature branch
3. Commit changes
4. Submit a pull request

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📜 License

This project is licensed under the MIT License – free to use, modify, and distribute.

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👨‍💻 Author

Nikhil Pise 🚀 Passionate about AI, ML, and building meaningful EdTech solutions.