.env.example

# Helius API Configuration
HELIUS_API_KEY=your_helius_api_key_here
HELIUS_MAX_RPS=200

# BirdEye API Configuration
BIRDEYE_API_KEY=your_birdeye_api_key_here
BIRDEYE_MAX_RPS=50

# API Usage Configuration
# API_USAGE_PERCENT: Percentage of max RPS to use for safety margin (default: 80)
# - Applied to both Helius and BirdEye APIs automatically
# - 80% provides good balance between performance and rate limit safety
# - Example: HELIUS_MAX_RPS=200 * 80% = 160 RPS actual usage
API_USAGE_PERCENT=80

# BirdEye Price History Timeframe
# Controls granularity of historical price data for ATH detection
# Options: 1m, 5m, 15m, 30m, 1H, 4H, 1D
# - 1D (default): Best API efficiency, ~1 API call per year of data, daily precision
# - 1H: More precise (hourly), but ~9 API calls per year of data
# - 1m: Highest precision (minute-level), but ~525 API calls per year (not recommended)
# Recommendation: Use '1D' for best performance unless you need intraday precision
BIRDEYE_PRICE_TIMEFRAME=1D

# Job Queue Configuration
# MAX_CONCURRENT_JOBS: Maximum number of analysis jobs running in parallel (default: 15)
# - Based on available RAM: 4 GB / ~227 MB per job = ~17 jobs max
# - Recommended: 15 (safe margin with ~600 MB for system)
# - DynamicRateLimiter will automatically distribute API rate limits across active jobs
# - With 15 jobs and 80% usage: (50 * 0.8) / 15 = ~2.67 RPS per job for BirdEye
MAX_CONCURRENT_JOBS=15