env.example

# Virtual Memory Manager Environment Configuration
# Copy this file to .env and modify the values as needed

# Backend Configuration
BACKEND_PORT=8080
BACKEND_HOST=0.0.0.0

# AI Predictor Configuration
PREDICTOR_PORT=5000
PREDICTOR_HOST=0.0.0.0
PREDICTOR_URL=http://localhost:5000

# Frontend Configuration
FRONTEND_PORT=3000
FRONTEND_HOST=localhost

# VMM Configuration
VMM_TOTAL_FRAMES=256
VMM_PAGE_SIZE=4096
VMM_TOTAL_PAGES=1024
VMM_REPLACEMENT_POLICY=CLOCK
VMM_ENABLE_AI=true

# Workload Configuration
WORKLOAD_TYPE=RANDOM
WORKLOAD_TOTAL_REQUESTS=1000
WORKLOAD_PAGE_RANGE=1000
WORKLOAD_STRIDE=1
WORKLOAD_ZIPF_ALPHA=1.0
WORKLOAD_LOCALITY_FACTOR=0.8
WORKLOAD_WORKING_SET_SIZE=100

# AI Model Configuration
AI_MODEL_TYPE=xgboost
AI_PREDICTION_THRESHOLD=0.7
AI_BATCH_SIZE=32
AI_MAX_PREDICTIONS=10

# Database Configuration (if using persistent storage)
DATABASE_URL=sqlite:///vmm.db
REDIS_URL=redis://localhost:6379

# Logging Configuration
LOG_LEVEL=INFO
LOG_FILE=logs/vmm.log

# Docker Configuration
DOCKER_NETWORK=vmm_network
DOCKER_VOLUME=vmm_data

# Production Configuration
NODE_ENV=development
DEBUG=true

# Render Deployment Configuration
RENDER=true
RENDER_EXTERNAL_URL=https://your-app.onrender.com

# Frontend Environment Variables (for Vite)
VITE_BACKEND_URL=http://localhost:8080
VITE_PREDICTOR_URL=http://localhost:5000
VITE_FRONTEND_PORT=3000

# Backend Environment Variables
BACKEND_PORT=8080
BACKEND_HOST=0.0.0.0
PREDICTOR_URL=http://localhost:5000

# AI Predictor Environment Variables
PREDICTOR_HOST=0.0.0.0
PREDICTOR_PORT=5000
MODEL_PATH=model.pkl
AI_MODEL_TYPE=xgboost
AI_PREDICTION_THRESHOLD=0.7