Add deployment configuration (Dockerfile, docker-compose, deployment scripts)

Dockerfile

@@ -0,0 +1,26 @@
+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    gcc \
+    g++ \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements and install Python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create necessary directories
+RUN mkdir -p backend/runs backend/tmp frontend/web
+
+# Expose port
+EXPOSE 8000
+
+# Run the application
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

@@ -91,6 +91,63 @@ Once the application is live on `http://localhost:8000`, follow these steps:
 
 ---
 
+## 🌐 Deployment Options
+
+### Quick Deploy (Recommended for Beginners)
+
+#### 1. Railway (Easiest - 5 minutes)
+```bash
+# Install Railway CLI
+npm install -g @railway/cli
+
+# Login and deploy
+railway login
+railway init automl-studio
+railway up
+```
+
+#### 2. Render (Free tier available)
+```bash
+# Run setup script
+bash setup-render.sh
+
+# Then deploy via Render dashboard
+# Go to render.com and connect your GitHub repo
+```
+
+#### 3. Docker (Most Flexible)
+```bash
+# Build and run with Docker Compose
+docker-compose up -d
+
+# Access at http://localhost:8000
+```
+
+### Advanced Deployment
+
+#### AWS/GCP/Azure
+- Use Elastic Beanstalk, App Engine, or App Service
+- Add RDS/Cloud SQL for database persistence
+- Use Cloud Storage for model artifacts
+
+#### Heroku
+```bash
+# Create Heroku app
+heroku create your-automl-studio
+
+# Deploy
+git push heroku main
+```
+
+### Production Considerations
+- **Database**: Add PostgreSQL for production data persistence
+- **Redis**: Required for background job queuing
+- **Storage**: Use cloud storage (S3, GCS) for large model files
+- **Scaling**: Consider load balancer for multiple instances
+- **Security**: Add authentication, rate limiting, and input validation
+
+---
+
 ## 🤝 Contributing
 
 Contributions are welcome! Please feel free to submit a Pull Request or open an Issue for any bugs, feature requests, or improvements.

deploy-railway.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+
+# Railway Deployment Script
+echo "🚀 Deploying AutoML Studio to Railway..."
+
+# Install Railway CLI if not present
+if ! command -v railway &> /dev/null; then
+    echo "Installing Railway CLI..."
+    npm install -g @railway/cli
+fi
+
+# Login to Railway (user will need to authenticate)
+railway login
+
+# Initialize Railway project
+railway init automl-studio
+
+# Set environment variables
+railway variables set REDIS_URL=redis://redis:6379/0
+
+# Deploy
+railway up
+
+echo "✅ Deployment complete!"
+echo "Your app will be available at the URL shown above"

docker-compose.yml

@@ -0,0 +1,40 @@
+version: '3.8'
+
+services:
+  web:
+    build: .
+    ports:
+      - "8000:8000"
+    volumes:
+      - ./backend/runs:/app/backend/runs
+      - ./backend/tmp:/app/backend/tmp
+    environment:
+      - REDIS_URL=redis://redis:6379/0
+    depends_on:
+      - redis
+    restart: unless-stopped
+
+  redis:
+    image: redis:7-alpine
+    ports:
+      - "6379:6379"
+    volumes:
+      - redis_data:/data
+    restart: unless-stopped
+
+  # Optional: Add PostgreSQL if using database features
+  # db:
+  #   image: postgres:15-alpine
+  #   environment:
+  #     POSTGRES_DB: automl
+  #     POSTGRES_USER: automl
+  #     POSTGRES_PASSWORD: your_password
+  #   volumes:
+  #     - postgres_data:/var/lib/postgresql/data
+  #   ports:
+  #     - "5432:5432"
+  #   restart: unless-stopped
+
+volumes:
+  redis_data:
+  # postgres_data:

setup-render.sh

@@ -0,0 +1,27 @@
+#!/bin/bash
+
+# Render Deployment Setup
+echo "🚀 Setting up AutoML Studio for Render deployment..."
+
+# Create render.yaml for multi-service deployment
+cat > render.yaml << EOF
+services:
+  - type: web
+    name: automl-studio
+    runtime: python3
+    buildCommand: pip install -r requirements.txt
+    startCommand: uvicorn backend.main:app --host 0.0.0.0 --port \$PORT
+    envVars:
+      - key: REDIS_URL
+        value: redis://redis:6379/0
+
+  - type: redis
+    name: automl-redis
+    ipAllowList: []  # Only accessible by other services
+EOF
+
+echo "✅ Render configuration created!"
+echo "1. Go to https://render.com"
+echo "2. Connect your GitHub repository"
+echo "3. Use the render.yaml file for deployment"
+echo "4. Or deploy the web service manually with the commands above"

test-deployment.sh

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+#!/bin/bash
+
+# Deployment Test Script
+echo "🧪 Testing AutoML Studio deployment readiness..."
+
+# Check if required files exist
+files=("requirements.txt" "backend/main.py" "frontend/app.py" "Dockerfile" "docker-compose.yml")
+for file in "${files[@]}"; do
+    if [ -f "$file" ]; then
+        echo "✅ $file found"
+    else
+        echo "❌ $file missing"
+        exit 1
+    fi
+done
+
+# Test Python imports
+echo "Testing Python dependencies..."
+python3 -c "
+import fastapi
+import uvicorn
+import pandas
+import sklearn
+import xgboost
+print('✅ All core dependencies available')
+"
+
+# Check if ports are available
+if lsof -Pi :8000 -sTCP:LISTEN -t >/dev/null; then
+    echo "⚠️  Port 8000 is already in use"
+else
+    echo "✅ Port 8000 is available"
+fi
+
+if lsof -Pi :6379 -sTCP:LISTEN -t >/dev/null; then
+    echo "⚠️  Port 6379 (Redis) is already in use"
+else
+    echo "✅ Port 6379 (Redis) is available"
+fi
+
+echo "🎉 Deployment test complete!"
+echo ""
+echo "Ready to deploy with:"
+echo "  Railway: railway up"
+echo "  Docker: docker-compose up -d"
+echo "  Local: bash run.sh"