AskMyNotes

AskMyNotes is a RAG-based study assistant. Upload a lecture PDF and:

1. Ask questions about it and get answers with page citations.
2. Generate a 5-question MCQ quiz from the content.

Architecture

┌────────────────┐      ┌──────────────────────┐      ┌───────────────┐
│   React UI      │ ───▶ │   FastAPI Backend     │ ───▶ │   ChromaDB     │
│ (Vite+Tailwind) │ ◀─── │ (LangChain + OpenAI)  │ ◀─── │ (vector store) │
└────────────────┘      └──────────────────────┘      └───────────────┘

• Upload: PDF is parsed with PyPDFLoader, split into 500-char chunks (50 overlap), embedded with OpenAI text-embedding-3-small, and stored in ChromaDB.
• Ask: User question is embedded, top-4 relevant chunks retrieved, answered by GPT-4o with page numbers returned.
• Quiz: Top chunks retrieved and sent to GPT-4o, which returns 5 MCQs as strict JSON.

Screenshots

Add screenshots here

• docs/screenshot-upload.png
• docs/screenshot-qna.png
• docs/screenshot-quiz.png

Local Development

Prerequisites

• Python 3.11
• Node.js 20
• Docker (optional, for containerized run)
• OpenAI API key

Backend

cd backend
cp .env.example .env   # add your OPENAI_API_KEY
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload

Frontend

cd frontend
cp .env.example .env
npm install
npm run dev

Using Docker Compose

docker compose up --build

Production Setup

Backend (AWS EC2)

1. Provision an EC2 instance (Ubuntu, Docker installed).
2. Create /home/<user>/askmynotes.env with OPENAI_API_KEY and ALLOWED_ORIGINS.
3. Configure GitHub Secrets: DOCKERHUB_USERNAME, DOCKERHUB_TOKEN, EC2_HOST, EC2_USER, EC2_SSH_KEY.
4. Push to main — GitHub Actions builds, pushes to Docker Hub, and redeploys via SSH.
5. Open port 8000 in the EC2 security group.

Frontend (Vercel)

1. Import the frontend directory as a Vercel project.
2. Set environment variable VITE_API_URL to your EC2 backend's public URL.
3. Deploy.

Environment Variables

Variable	Location	Description
OPENAI_API_KEY	backend	OpenAI API key
ALLOWED_ORIGINS	backend	Comma-separated CORS origins
CHROMA_DIR	backend	ChromaDB persistence path
VITE_API_URL	frontend	Backend API base URL

Step-by-Step Setup Guide (Beginner)

Step 1: Install prerequisites

• Install Python 3.11 from python.org
• Install Node.js 20 from nodejs.org
• Install Docker Desktop (optional)
• Get an OpenAI API key from platform.openai.com

Step 2: Project files

Extract this project to a folder called askmynotes.

Step 3: Set up the backend

1. Open a terminal in askmynotes/backend
2. Run: cp .env.example .env
3. Open .env and paste your OpenAI key after OPENAI_API_KEY=
4. Create a virtual environment:
   • python -m venv venv
   • Activate it: source venv/bin/activate (Mac/Linux) or venv\Scripts\activate (Windows)
5. Install dependencies: pip install -r requirements.txt
6. Start the server: uvicorn main:app --reload
7. Visit http://localhost:8000/health — you should see {"status": "ok"}

Step 4: Set up the frontend

1. Open a new terminal in askmynotes/frontend
2. Run: cp .env.example .env (leave VITE_API_URL=http://localhost:8000)
3. Install dependencies: npm install
4. Start the dev server: npm run dev
5. Open the URL shown (usually http://localhost:5173)

Step 5: Try it out

1. Go to the "Upload" tab and upload a PDF of lecture notes
2. Switch to "Ask Questions" and type a question — note the cited page numbers
3. Switch to "Quiz" and click "Generate 5 MCQs" — click an option to see if it's correct

Step 6 (Optional): Run everything with Docker

1. From the project root: docker compose up --build
2. Backend runs on port 8000, frontend on port 5173

Step 7: Deploy to production

1. Push your code to a GitHub repository
2. Set up an AWS EC2 instance with Docker installed
3. Add the required secrets in GitHub repo settings → Secrets and variables → Actions:
   • DOCKERHUB_USERNAME, DOCKERHUB_TOKEN
   • EC2_HOST, EC2_USER, EC2_SSH_KEY
4. Push to the main branch — the GitHub Action will build and deploy automatically
5. Deploy the frontend to Vercel, setting VITE_API_URL to your EC2 backend URL