PaperBrain — Your Intelligent Study Assistant

AI-powered learning platform with RAG, Quiz, Flashcards, Explain, Resume — and local n8n AI Agent automation.

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🌐 Spacy Demo Live :

🔗 Hugging Face Space: [https://huggingface.co/spaces/ApyHTML19/PaperBrainAI]

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✨ Features

Feature	Description
💬 General Chat	AI-powered study assistant (Qwen 2.5-72B)
📄 RAG Mode	Ask questions based on your uploaded documents
🧪 Quiz	Auto-generated MCQ quizzes on any topic
🃏 Flashcards	Smart flashcards for memorization
💡 Explain	Concept explanations at beginner / intermediate / advanced level
📝 Resume	Auto-summarize any text or document
📁 Document Manager	Upload PDF, TXT, DOCX — indexed per user
👤 Auth	JWT-based register/login with user isolation
📊 Profile & Stats	Quiz history, streaks, progression tracking
🔄 n8n AI Agent	Local AI Agent with Ollama llama3.1/Qwen 2.5 (Locally/Pre-trained Model on HuggingFace + 5 tools

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🏗️ Architecture

PaperBrain/
├── backend/                  # FastAPI Python backend
│   ├── app/
│   │   ├── auth/
│   │   │   ├── jwt_handler.py     # JWT token creation/decoding
│   │   │   └── middleware.py      # get_current_user dependency
│   │   ├── db/
│   │   │   ├── database.py        # SQLite + SQLAlchemy setup
│   │   │   ├── models.py          # User, QuizResult, StudySession models
│   │   │   └── crud.py            # DB operations
│   │   ├── tools/                 # AI tool modules
│   │   ├── agent.py               # Main AI dispatcher
│   │   ├── ingest.py              # Document ingestion + chunking
│   │   ├── rag.py                 # ChromaDB vector store
│   │   ├── router_service.py      # All API routes
│   │   ├── schemas.py             # Pydantic request models
│   │   └── main.py                # FastAPI app entry point
│   ├── Dockerfile
│   └── requirements.txt
├── frontend/                 # React frontend
│   └── src/
│       └── pages/
│           ├── Chat.jsx
│           ├── Quiz.jsx
│           ├── Flashcards.jsx
│           ├── Documents.jsx
│           └── Profile.jsx
├── n8n/                      # Local n8n AI Agent workflows
│   └── workflows/
│       └── PaperBrain.json
└── docs/
    ├── logo.png
    └── n8n-workflow.png

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🔄 n8n AI Agent (Local)

PaperBrain includes a local n8n AI Agent powered by Ollama llama3.1 that orchestrates all learning tools automatically.

Workflow Architecture

[Input Postman / Frontend]
        ↓
  [AI Agent For RAG]  ←→  [Ollama - llama3.1]
        ↓
  ┌─────┴──────────────────────────────┐
  │                                    │
[Flashcards Tool]  [Explain Tool]  [RAG Tool]  [Resume Tool]  [Quiz Tool]
        ↓
[Output Frontend]

Tools disponibles dans l'agent

Tool	Description
🃏 Flashcards Tool	Generate flashcards on any topic
💡 Explain Tool	Explain a concept at any level
📄 RAG Tool	Search course documents for answers
📝 Resume Tool	Summarize topics automatically
🧪 Quiz Tool	Generate MCQ quiz questions

Setup n8n local

# Install n8n
npm install -g n8n

# Start n8n
n8n start
# → Access at http://localhost:5678

# Install Ollama
# https://ollama.com/download

# Pull llama3.1
ollama pull llama3.1

Import the workflow

1. Open n8n at http://localhost:5678
2. Go to Workflows → Import
3. Import n8n/workflows/PaperBrain.json
4. Configure the Ollama node with your local URL: http://localhost:11434
5. Publish the workflow

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🚀 Tech Stack

Backend

• FastAPI — REST API
• SQLite + SQLAlchemy — Database
• ChromaDB — Vector store for RAG
• HuggingFace InferenceClient — Cloud AI (Qwen2.5-72B)
• python-jose — JWT authentication
• pdfplumber + python-docx — Document parsing

Frontend

• React 18 — UI framework
• Vite — Build tool

Local AI Automation

• n8n — AI Agent workflow automation
• Ollama — Local LLM runtime
• llama3.1 — Local AI model

Deployment

• Hugging Face Spaces — Docker deployment

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⚙️ Local Setup

Prerequisites

• Python 3.10+
• Node.js 18+
• Ollama (for n8n local AI)

1. Clone the repo

git clone https://github.com/ApyHtml20/PaperBrain.git
cd PaperBrain

2. Backend

cd backend
pip install -r requirements.txt

Create .env:

HF_TOKEN=your_huggingface_token
HF_MODEL=Qwen/Qwen2.5-72B-Instruct
SECRET_KEY=your_secret_key_here

uvicorn app.main:app --reload --port 8000

3. Frontend

cd frontend
npm install
npm run dev

4. n8n + Ollama

ollama pull llama3.1
n8n start

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🔌 API Endpoints

Auth

Method	Route	Description
POST	/api/auth/register	Create new account
POST	/api/auth/login	Login and get JWT token

Learning (🔒 Auth required)

Method	Route	Description
POST	/api/chat	General AI chat
POST	/api/rag-qa	Chat with your documents
POST	/api/quiz	Generate MCQ quiz
POST	/api/flashcards	Generate flashcards
POST	/api/explain	Explain a concept
POST	/api/resume	Summarize text

Documents (🔒 Auth required)

Method	Route	Description
GET	/api/documents	List your documents
POST	/api/upload	Upload PDF/TXT/DOCX
DELETE	/api/documents/{filename}	Delete a document

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🐳 Docker / HF Spaces

FROM python:3.11-slim
WORKDIR /code
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

HF Spaces secrets (Settings → Variables and secrets):

HF_TOKEN=...
HF_MODEL=Qwen/Qwen2.5-72B-Instruct
SECRET_KEY=...

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🔐 Security

• Passwords hashed with SHA-256 + random salt
• JWT tokens expire after 24 hours
• All routes protected by auth middleware
• Documents isolated by user_id in ChromaDB
• Files stored in documents/{user_id}/

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