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📄🎙️ PaperParser

PaperParser transforms academic research papers into podcasts 🎧 and PowerPoint presentations 📊.
By combining AI summarization and automated content generation, it makes scholarly content easier to consume and share.


🚀 Features

  • 🎧 Podcast Generation – Listen to research papers in audio format
  • 📊 Presentation Creation – Auto-generate slide decks with key insights
  • 📄 PDF Parsing – Extract text and structure from uploaded research papers
  • ☁️ Cloud Integration – Secure storage and authentication with Supabase

🛠️ Technologies Used

🔙 Backend

  • Node.js + Express.js – Core API server
  • 🧠 Gemini API – Summarization and content generation
  • 📄 PyMuPDF – High-quality PDF text parsing
  • ☁️ Supabase – Database + authentication layer
  • 🐳 Docker – Containerized backend for easy deployment

🎨 Frontend

  • ⚛️ Next.js (React + TypeScript) – Modern frontend framework
  • 🌀 Tailwind CSS – Utility-first styling for responsive UI

⚙️ Installation

1️⃣ Clone the Repository

git clone https://github.com/P1Manav/PaperParser.git
cd PaperParser

2️⃣ Backend Setup (Dockerized 🐳)

Navigate to backend:

cd backend

Create a .env file (sample):

SUPABASE_URL=
SUPABASE_SERVICE_ROLE_KEY=
GEMINI_API_KEY=
google_api_key=
PORT=5000
NODE_ENV=

Build Docker image:

docker build -t paperparser_image .

Run the container:

docker run --env-file .env -p 5000:5000 --name paperparser_container paperparser_image

📌 Backend runs at: http://localhost:5000


3️⃣ Frontend Setup

Navigate to frontend:

cd ../frontend

Create .env.local file (sample):

NEXT_PUBLIC_SUPABASE_URL=
NEXT_PUBLIC_SUPABASE_ANON_KEY=
GEMINI_API_KEY=
NEXT_PUBLIC_API_URL=http://localhost:5000

Install dependencies:

npx yarn install

Run development server:

npx yarn dev

📌 Frontend runs at: http://localhost:3000


🎯 Usage

  1. 📄 Upload a PDF in the frontend
  2. ⚙️ Choose output → Podcast 🎧 or Presentation 📊
  3. ⬇️ Download or play the result directly

🤝 Contributing

Contributions are welcome! 🚀

  • Open an issue for bugs or feature requests
  • Submit a PR to help improve PaperParser

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  • TypeScript 79.9%
  • Python 11.0%
  • JavaScript 5.0%
  • PLpgSQL 2.2%
  • CSS 1.7%
  • Dockerfile 0.2%