Configuring the SDK
API keys and clients
By default, the SDK looks for the OPENAI_API_KEY environment variable for LLM requests and tracing, as soon as it is imported. If you are unable to set that environment variable before your app starts, you can use the set_default_openai_key() function to set the key.
Alternatively, you can also configure an OpenAI client to be used. By default, the SDK creates an AsyncOpenAI instance, using the API key from the environment variable or the default key set above. You can change this by using the set_default_openai_client() function.
from openai import AsyncOpenAI
from agents import set_default_openai_client
custom_client = AsyncOpenAI(base_url="...", api_key="...")
set_default_openai_client(custom_client)
Finally, you can also customize the OpenAI API that is used. By default, we use the OpenAI Responses API. You can override this to use the Chat Completions API by using the set_default_openai_api() function.
Tracing
Tracing is enabled by default. It uses the OpenAI API keys from the section above by default (i.e. the environment variable or the default key you set). You can specifically set the API key used for tracing by using the set_tracing_export_api_key function.
You can also disable tracing entirely by using the set_tracing_disabled() function.
Debug logging
The SDK has two Python loggers without any handlers set. By default, this means that warnings and errors are sent to stdout, but other logs are suppressed.
To enable verbose logging, use the enable_verbose_stdout_logging() function.
Alternatively, you can customize the logs by adding handlers, filters, formatters, etc. You can read more in the Python logging guide.
import logging
logger = logging.getLogger("openai.agents") # or openai.agents.tracing for the Tracing logger
# To make all logs show up
logger.setLevel(logging.DEBUG)
# To make info and above show up
logger.setLevel(logging.INFO)
# To make warning and above show up
logger.setLevel(logging.WARNING)
# etc
# You can customize this as needed, but this will output to `stderr` by default
logger.addHandler(logging.StreamHandler())
Sensitive data in logs
Certain logs may contain sensitive data (for example, user data). If you want to disable this data from being logged, set the following environment variables.
To disable logging LLM inputs and outputs:
To disable logging tool inputs and outputs: