Configuration Guide¶

Learn how to configure Amega AI for your specific needs.

Configuration File¶

Amega AI uses a YAML configuration file (config.yml) for managing settings. Create this file in your project root:

# config.yml

# API Configuration
api:
  host: localhost
  port: 8000
  debug: false
  api_key: your-api-key

# Model Settings
model:
  default_framework: pytorch
  cache_dir: ~/.amega/models
  max_batch_size: 32
  device: cuda  # or cpu

# Training
training:
  default_epochs: 10
  learning_rate: 0.001
  optimizer: adam
  early_stopping:
    enabled: true
    patience: 3
    min_delta: 0.001

# Logging
logging:
  level: INFO
  file: logs/amega.log
  format: '%(asctime)s - %(name)s - %(levelname)s - %(message)s'

# Security
security:
  enable_ssl: true
  ssl_cert: path/to/cert.pem
  ssl_key: path/to/key.pem

Environment Variables¶

You can also configure Amega AI using environment variables:

# API Settings
export AMEGA_API_KEY=your-api-key
export AMEGA_HOST=localhost
export AMEGA_PORT=8000

# Model Settings
export AMEGA_MODEL_FRAMEWORK=pytorch
export AMEGA_DEVICE=cuda

# Security
export AMEGA_SSL_ENABLED=true

Configuration Priority¶

Settings are loaded in the following order (highest priority first):

Environment variables
Command line arguments
Configuration file
Default values

Example Usage¶

from amega_ai import Config

# Load configuration
config = Config.load("config.yml")

# Access configuration values
api_key = config.api.key
model_framework = config.model.framework

# Override settings
config.model.device = "cpu"
config.save()

Advanced Configuration¶

Custom Model Configuration¶

# config.yml

models:
  sentiment_analysis:
    architecture: transformer
    hidden_size: 768
    num_layers: 12
    dropout: 0.1

  image_classification:
    architecture: resnet
    num_classes: 1000
    pretrained: true

Distributed Training¶

# config.yml

distributed:
  enabled: true
  backend: nccl
  world_size: 4
  master_addr: localhost
  master_port: 29500

Monitoring Configuration¶

# config.yml

monitoring:
  prometheus:
    enabled: true
    port: 9090

  grafana:
    enabled: true
    dashboard_dir: dashboards/

Security Best Practices¶

Never commit API keys or sensitive data
Use environment variables for secrets
Enable SSL in production
Regularly rotate API keys
Set appropriate file permissions