DEPLOYMENT.md

🚀 Deployment Guide

This guide covers different deployment options for the LangChain Agent API.

📋 Prerequisites

• Node.js 18+ (for manual deployment)
• Docker & Docker Compose (for containerized deployment)
• Redis server
• OpenAI API key

🔧 Build Process

The project uses TypeScript and builds to the dist/ folder:

# Clean previous build
npm run clean

# Build for production
npm run build

# Check build output
ls -la dist/

🖥️ Manual Deployment

1. Prepare Environment

# Clone repository
git clone <your-repo-url>
cd langchain-agent-api

# Install dependencies
npm ci --only=production

# Copy environment file
cp .env.production.example .env.production
# Edit .env.production with your values

2. Build Application

npm run build

3. Start Services

# Start Redis (if not using external Redis)
redis-server

# Start the application
npm run start:prod

🐳 Docker Deployment

Option 1: Docker Compose (Recommended)

# Copy environment file
cp .env.production.example .env

# Edit .env with your values
nano .env

# Start all services
docker-compose up -d

# Check logs
docker-compose logs -f app

# Stop services
docker-compose down

Option 2: Manual Docker

# Build image
docker build -t langchain-agent-api .

# Run Redis
docker run -d --name redis -p 6379:6379 redis:7-alpine

# Run application
docker run -d \
  --name langchain-api \
  -p 3000:3000 \
  --link redis:redis \
  --env-file .env \
  langchain-agent-api

☁️ Cloud Deployment

Heroku

# Install Heroku CLI
# Create Heroku app
heroku create your-app-name

# Add Redis addon
heroku addons:create heroku-redis:mini

# Set environment variables
heroku config:set OPENAI_API_KEY="your-key"
heroku config:set NODE_ENV=production

# Deploy
git push heroku main

Railway

# Install Railway CLI
npm install -g @railway/cli

# Login and deploy
railway login
railway init
railway up

DigitalOcean App Platform

1. Connect your GitHub repository
2. Set build command: npm run build
3. Set run command: npm run start:prod
4. Add environment variables
5. Add Redis database

🔍 Health Checks

The application includes health check endpoints:

# Basic health check
curl http://localhost:3000/

# Tool status
curl http://localhost:3000/ai/chat-with-memory/tools

📊 Monitoring

Logs

# Docker Compose logs
docker-compose logs -f app

# Docker logs
docker logs -f langchain-api

# PM2 (if using PM2)
pm2 logs

Metrics

Monitor these key metrics:

• Response time
• Token usage
• Error rates
• Redis memory usage
• Tool success rates

🔒 Security Considerations

Environment Variables

• Never commit .env files
• Use strong Redis passwords in production
• Rotate API keys regularly
• Use HTTPS in production

Network Security

# Use reverse proxy (nginx example)
server {
    listen 80;
    server_name your-domain.com;
    
    location / {
        proxy_pass http://localhost:3000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

🚨 Troubleshooting

Common Issues

1. Build fails

   npm run clean
   npm run build

2. Redis connection error

   • Check Redis is running
   • Verify REDIS_URL in environment

3. OpenAI API errors

   • Verify API key is correct
   • Check API quota/billing

4. Port already in use

   # Find process using port
   lsof -i :3000
   # Kill process
   kill -9 <PID>

Debug Mode

# Enable verbose logging
export AGENT_VERBOSE=true
export NODE_ENV=development

# Run with debug
npm run dev

📈 Scaling

Horizontal Scaling

# docker-compose.yml
services:
  app:
    deploy:
      replicas: 3
    # ... other config
  
  nginx:
    image: nginx:alpine
    # Load balancer config

Vertical Scaling

# Increase memory limits
docker run --memory=2g langchain-agent-api

🔄 Updates

# Pull latest changes
git pull origin main

# Rebuild
npm run build

# Restart services
docker-compose restart app

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For more help, check the main README.md or create an issue in the repository.