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Configuration Guide

Configure AgenticAI for your environment

Flexible configuration options for 400+ modules and 237 enterprise features

Enterprise Configuration

For advanced options including multi-tenant, high-availability, and compliance settings, see Enterprise Documentation.

1. Configuration Methods

You can configure AgenticAI in three ways:

  1. Programmatically – Using set_config() from agenticaiframework.configurations
  2. Configuration File – Using the ConfigurationManager class
  3. Environment Variables – Setting variables before running your application

2. Common Configuration Keys

Key Description Example
llm_provider LLM provider to use "openai"
api_key API key for LLM provider "sk-xxxx"
memory_backend Memory storage backend "in_memory"
log_level Logging verbosity "INFO"
default_agent Default agent name "default_agent"

3. Programmatic Configuration

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from agenticaiframework.configurations import ConfigurationManager

config = ConfigurationManager()
config.set_config("LLM", {"provider": "openai", "model": "gpt-4"})
config.set_config("Logging", {"log_level": "INFO"})

4. Using Environment Variables

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export OPENAI_API_KEY=your_api_key_here
export ANTHROPIC_API_KEY=your_api_key_here
export AGENTICAI_LOG_LEVEL=INFO

5. Default Configuration

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CONFIG = {
    "llm_provider": "openai",
    "api_key": "",
    "memory_backend": "in_memory",
    "log_level": "INFO",
    "default_agent": "default_agent"
}

6. Advanced Configuration

  • Multiple LLM Providers – Register multiple providers and switch dynamically
  • Custom Memory Backends – Implement custom backends for persistence
  • Logging – Adjust log_level to "DEBUG" for detailed logs

7. Verifying Configuration

Python
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from agenticaiframework.configurations import ConfigurationManager

config = ConfigurationManager()
logger.info(config.get_config("LLM"))

8. Environment-Specific Configurations

Maintain separate configurations for different environments:

  • config_dev.py for development
  • config_staging.py for staging
  • config_prod.py for production

Load dynamically based on environment:

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import os
from agenticaiframework.configurations import ConfigurationManager

env = os.getenv("AGENTICAI_ENV", "dev")
config = ConfigurationManager()

if env == "prod":
    config.set_config("Logging", {"log_level": "WARNING"})
else:
    config.set_config("Logging", {"log_level": "DEBUG"})

9. Dynamic Configuration Updates

Update configuration values at runtime:

Python
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from agenticaiframework.configurations import ConfigurationManager

config = ConfigurationManager()
config.set_config("Logging", {"log_level": "DEBUG"})
logger.info(config.get_config("Logging"))

10. Secrets Management

For sensitive values like API keys, use a secrets manager:

  • AWS Secrets Manager
  • HashiCorp Vault
  • Azure Key Vault
  • Google Secret Manager
Python
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import os

# Load from environment (recommended)
api_key = os.getenv("OPENAI_API_KEY")

11. Best Practices

Configuration Best Practices

  • Store API keys securely (environment variables or secret managers)
  • Never commit sensitive data to version control
  • Use different configurations for dev/staging/production
  • Document all configuration keys
  • Use .env files for local development with python-dotenv