# Fetch ML Configuration Example
# Copy this file to config.yaml and customize for your environment

auth:
  enabled: true
  api_keys:
    # Example API key (replace with real hashed keys)
    admin:
      hash: "5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8"  # "password"
      admin: true
      roles: ["admin"]
      permissions:
        "*": true

server:
  host: "localhost"
  port: 8080

database:
  type: "sqlite"
  connection: "data/fetch_ml.db"
  host: ""
  port: 5432
  username: ""
  password: ""
  database: "fetch_ml"

redis:
  url: "redis://localhost:6379"
  host: "localhost"
  port: 6379
  password: ""
  db: 0
  pool_size: 10
  max_retries: 3

logging:
  level: "info"
  file: "logs/fetch_ml.log"
  format: "text"
  console: true

security:
  secret_key: "your-secret-key-at-least-16-chars"
  jwt_expiry: "24h"
  rate_limit:
    enabled: false
    requests_per_minute: 60

containers:
  runtime: "podman"
  registry: "docker.io"
  pull_policy: "missing"
  resources:
    cpu_limit: "2"
    memory_limit: "4Gi"
    gpu_limit: 1

storage:
  data_path: "data"
  results_path: "results"
  temp_path: "/tmp/fetch_ml"
  cleanup:
    enabled: true
    max_age_hours: 168
    max_size_gb: 10