Note Taker AI 🎙️

An AI-powered note-taking application that transcribes and summarizes audio recordings using AssemblyAI and OpenAI. Built as an example application for the Render AI Agent example library.

🚀 New? Start Here!

Want to run this locally in 5 minutes? → QUICKSTART.md

The quickstart guide walks you through getting everything running with Docker Compose in just a few commands!

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Table of Contents

• Deploy to Render
• Features
• Repository Structure
• Quick Start with Docker
• Docker Commands
• Troubleshooting
• Additional Documentation
• Contributing
• License

🚀 Deploy to Render

This project is pre-configured for one-click deployment to Render using the included render.yaml blueprint.

What you get:

• ✅ Next.js frontend with browser-based audio recording
• ✅ Flask backend with AssemblyAI and OpenAI integration
• ✅ Separate frontend and backend services
• ✅ Auto-scaling and health checks
• ✅ Environment variable management

Deployment steps:

1. Fork this repository to your GitHub account

2. Create a new Blueprint Instance on Render:

   • Go to Render Dashboard
   • Click "New" → "Blueprint Instance"
   • Connect your forked repository
   • Select branch (usually main)

3. Configure environment variables:

   • Render will auto-detect render.yaml
   • You'll be prompted to enter:
     • ASSEMBLYAI_API_KEY (Get one here)
     • OPENAI_API_KEY (Get one here)
   • Optional: OPENAI_MODEL (defaults to gpt-4o-mini)

4. Deploy:

   • Click "Apply" to create all services
   • Render will:
     • Build and deploy Flask backend
     • Build and deploy Next.js frontend
     • Automatically link services together (frontend will auto-connect to backend!)

5. Access your deployed app:

   • Frontend: https://your-app-name-frontend.onrender.com
   • Backend API: https://your-app-name-backend.onrender.com
   • That's it! The app works immediately - no manual configuration needed! 🎉

Cost Estimate (Render Free Tier):

• 2 Web Services (frontend + backend): Free
• AssemblyAI API: Pay-per-use (~$0.05 per audio hour)
• OpenAI API: Pay-per-use (~$0.01-0.05 per summary)
• Total: ~$0/month recurring (free tier) + usage-based API costs

✨ Features

• 🎤 Browser-based audio recording - Record directly in your browser, no downloads needed
• ⚡ Lightning-fast transcription - Powered by AssemblyAI for accurate speech-to-text
• 🤖 AI-powered summaries - Get key insights, important points, and action items with OpenAI
• 📊 Intelligent chunking - Handles transcriptions of any length with automatic text chunking (no context overflow!)
• 🎨 Beautiful UI - Inspired by Render.com's clean, modern design with markdown support
• 🐳 Docker-ready - Easy deployment with Docker Compose
• ☁️ Render-optimized - Deploy to production with a single blueprint file

📁 Repository Structure

.
├── backend/               # Flask + Python API (transcription + summarization)
│   ├── app.py             # Flask application
│   ├── pyproject.toml     # uv dependencies
│   ├── services/          # AssemblyAI and OpenAI integrations
│   │   ├── assemblyai_service.py
│   │   └── openai_service.py
│   ├── Dockerfile         # Backend container
│   └── ...
├── frontend/              # Next.js app (audio recorder + results viewer)
│   ├── app/
│   │   ├── page.tsx       # Main page
│   │   ├── layout.tsx     # App layout
│   │   └── globals.css    # Global styles
│   ├── components/
│   │   ├── AudioRecorder.tsx  # Audio recording component
│   │   └── ResultsViewer.tsx  # Results display
│   ├── lib/
│   │   └── api.ts         # API client
│   ├── Dockerfile         # Nginx-served production build
│   └── next.config.ts     # Next.js configuration
├── docker-compose.yml     # Full-stack local development
├── render.yaml            # Production deployment configuration (Render.com)
├── QUICKSTART.md          # Quick start guide
└── README.md

🚀 Quick Start with Docker

For detailed step-by-step instructions, see QUICKSTART.md

TL;DR:

# 1. Clone the repo
git clone <your-repo-url>
cd render-meeting-notes-agent

# 2. Create .env file with your API keys
cat > .env << 'EOF'
ASSEMBLYAI_API_KEY=your-key-here
OPENAI_API_KEY=sk-your-key-here
OPENAI_MODEL=gpt-4o-mini
BACKEND_PORT=3100
FRONTEND_PORT=3000
EOF

# 3. Start everything
docker compose up -d

# 4. Open http://localhost:3000

This starts:

• ✅ Flask backend API (port 3100)
• ✅ Next.js frontend UI (port 3000)
• ✅ Browser-based audio recording ready to use

📦 Docker Commands

Start all services:

docker compose up -d

Stop all services:

docker compose down

View logs:

# All services
docker compose logs -f

# Specific service
docker compose logs -f backend
docker compose logs -f frontend

Rebuild after code changes:

docker compose up -d --build

🐛 Troubleshooting

1. Docker port conflicts:

# Check what's using the port
lsof -i :3100  # or :3000

# Change ports in .env file or docker-compose.yml

2. Backend connection errors:

# Ensure backend is running
docker compose ps

# Check backend logs
docker compose logs backend

3. AssemblyAI API errors:

• Verify your API key is valid at https://www.assemblyai.com/
• Check your AssemblyAI account has credits
• Ensure API key is properly set in .env or environment variables

4. OpenAI API errors:

• Verify your API key is valid at https://platform.openai.com/api-keys
• Check your OpenAI account has credits
• Ensure correct model name in configuration (e.g., gpt-4o-mini)

5. Frontend can't reach backend:

• For local dev: Frontend should connect to http://localhost:3100
• For Docker: Check NEXT_PUBLIC_API_URL in docker-compose.yml build args
• For Render: Services are auto-linked via render.yaml

Getting more help:

1. Check service logs: docker compose logs <service-name>
2. Verify all environment variables are set correctly
3. Ensure Docker containers are healthy: docker compose ps
4. See detailed troubleshooting in backend/README.md

📚 Additional Documentation

• QUICKSTART.md - 🚀 Get started in 5 minutes with Docker Compose
• ARCHITECTURE.md - 🏗️ System architecture and design decisions
• backend/README.md - Backend API documentation
• frontend/README.md - Frontend component documentation

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT