NotesAI

An AI-powered study guide generator that transforms lecture PDFs into beautifully formatted, comprehensive study notes.

Overview

NotesAI helps students convert their lecture slides and PDFs into aesthetic, exam-ready study guides. Unlike simple summarization tools, NotesAI preserves all lecture content while restructuring it for optimal learning with key terms, organized sections, examples, and quiz questions.

Features

• PDF Upload and Processing: Upload lecture PDFs up to 50MB for automatic processing
• Intelligent Text Extraction: Preserves document structure including headings, formulas, and page references
• RAG Pipeline: Retrieval-Augmented Generation architecture using Pinecone vector storage and Claude for accurate, context-aware note generation
• AI-Powered Note Generation: Uses Claude with a Map-Reduce pattern to generate comprehensive, well-structured notes
• Real-time Progress Tracking: Monitor processing status as your notes are generated
• Clean Typography: Premium fonts (EB Garamond, Inter) for readable, aesthetic output

Tech Stack

Frontend

• Next.js 16 with React 19
• TypeScript
• Tailwind CSS 4
• Lucide React icons

Backend

• FastAPI (Python 3.11)
• Anthropic Claude API (claude-sonnet-4-5-20250929)
• OpenAI Embeddings (text-embedding-3-small)
• Pinecone Vector Database
• Supabase (PostgreSQL)
• PyMuPDF for PDF processing

Project Structure

notes_ai/
├── backend/
│   ├── app/
│   │   ├── main.py              # FastAPI app entry point
│   │   ├── api/routes/          # API endpoints
│   │   ├── services/            # Business logic
│   │   ├── core/                # Config, database, RAG engine
│   │   └── models/              # Pydantic schemas
│   ├── requirements.txt
│   └── .env.example
├── frontend/
│   ├── app/                     # Next.js pages and layouts
│   ├── components/              # React components
│   ├── lib/                     # Utilities and API client
│   ├── package.json
│   └── .env.example
└── README.md

Getting Started

Prerequisites

• Python 3.11+
• Node.js 18+
• API keys for: Supabase, Anthropic, OpenAI, Pinecone

Backend Setup

cd backend

# Create and activate virtual environment
python -m venv venv
venv\Scripts\activate        # Windows
source venv/bin/activate     # macOS/Linux

# Install dependencies
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env
# Edit .env with your API keys

# Run development server
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Frontend Setup

cd frontend

# Install dependencies
npm install

# Configure environment variables
cp .env.example .env.local
# Edit .env.local with your backend URL

# Run development server
npm run dev

The frontend will be available at http://localhost:3000 and the backend API at http://localhost:8000.

Environment Variables

Backend

Variable	Description
SUPABASE_URL	Supabase project URL
SUPABASE_ANON_KEY	Supabase anonymous key
SUPABASE_SERVICE_KEY	Supabase service role key
ANTHROPIC_API_KEY	Anthropic API key for Claude
OPENAI_API_KEY	OpenAI API key for embeddings
PINECONE_API_KEY	Pinecone API key
PINECONE_ENVIRONMENT	Pinecone environment (e.g., us-east-1)
MAX_FILE_SIZE_MB	Maximum upload file size (default: 50)
UPLOAD_DIR	Directory for uploaded files
FRONTEND_URL	Frontend URL for CORS

Frontend

Variable	Description
NEXT_PUBLIC_API_URL	Backend API URL

API Endpoints

Method	Endpoint	Description
POST	/api/upload	Upload a PDF file
GET	/api/status/{doc_id}	Check processing status
POST	/api/notes/generate/{doc_id}	Trigger note generation
GET	/api/notes/{doc_id}	Retrieve generated notes
GET	/health	Health check

Deployment

Backend (Render)

1. Connect your GitHub repository to Render
2. Set root directory to backend
3. Configure build command: pip install -r requirements.txt
4. Configure start command: uvicorn app.main:app --host 0.0.0.0 --port $PORT
5. Add all environment variables from .env.example

Frontend (Vercel)

1. Import your repository to Vercel
2. Set root directory to frontend
3. Add NEXT_PUBLIC_API_URL environment variable pointing to your Render backend URL

License

MIT