Configuration

This section provides detailed guidance on configuring the pyagentai client, including setting up logging and managing API credentials.

Configuring the Client

The AgentAIClient can be configured in several ways to suit your application’s needs.

Using AgentAIConfig

The AgentAIConfig class allows you to define all client settings in one place. You can create an instance of this class and pass it to the AgentAIClient constructor.

from pyagentai import AgentAIClient, AgentAIConfig

# Create a custom configuration
config = AgentAIConfig(
    api_key="your_custom_api_key",
    timeout=120.0
)

# Initialize the client with the custom configuration
client = AgentAIClient(config=config)

Direct Initialization

For quick setup, you can pass the API key directly to the AgentAIClient constructor. Other settings will use default values.

from pyagentai import AgentAIClient

# Initialize the client with an API key
client = AgentAIClient(api_key="your_agentai_api_key")

Environment Variables

The client can also be configured using environment variables. This is particularly useful in production environments.

AGENTAI_API_KEY: Your agent.ai API key.
AGENTAI_API_URL: The base URL for the agent.ai API.
AGENTAI_WEB_URL: The URL for the agent.ai web application.

import os
from pyagentai import AgentAIClient

# Set environment variables before initializing the client
os.environ["AGENTAI_API_KEY"] = "your_api_key_from_env"

# The client will automatically pick up the settings
client = AgentAIClient()

Loading from YAML

For more complex configurations, you can load settings from a YAML file.

config.yaml

api_key: "your_api_key_from_yaml"
timeout: 90.0

from pyagentai import AgentAIConfig, AgentAIClient

# Load configuration from a YAML file
config = AgentAIConfig.from_yaml("config.yaml")
client = AgentAIClient(config=config)

Configuring Logging

pyagentai uses the structlog library for logging, which is highly configurable.

Using the configure_logging function

The easiest way to set up logging is with the configure_logging function from the pyagentai package.

from pyagentai import configure_logging

# Configure logging with a specific log level and format
configure_logging(log_level="DEBUG", log_format="json")

Logging with Environment Variables

You can also configure logging using environment variables, which is ideal for containerized or production environments.

AGENTAI_LOG_LEVEL: Log level (e.g., DEBUG, INFO, WARNING).
AGENTAI_LOG_FORMAT: Log format (console or json).
AGENTAI_LOG_FILE_ENABLED: Set to true to enable file logging.
AGENTAI_LOG_DIR: Directory to store log files.
AGENTAI_LOG_FILE_NAME: Name of the log file.

Example:

export AGENTAI_LOG_LEVEL="DEBUG"
export AGENTAI_LOG_FILE_ENABLED="true"
export AGENTAI_LOG_DIR="/var/log/pyagentai"

The library will automatically apply these settings when it is imported.