How can I configure error logging for the Anthropic API in Python

1. Enable debug-level logging: You can enable debug-level logging by setting the `ANTHROPIC_LOG` environment variable to `"debug"`:

bash
export ANTHROPIC_LOG=debug

This will output detailed logs, including any errors or exceptions that occur when using the Anthropic API.

2. Use a logging library: You can also configure logging using a Python logging library, such as the built-in `logging` module. Here's an example:

python
import logging
import anthropic

logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s: %(message)s')

client = anthropic.Anthropic()

try:
    response = client.completions.create(
        prompt=f"{anthropic.HUMAN_PROMPT} Your prompt here{anthropic.AI_PROMPT}",
        max_tokens_to_sample=300,
        model="claude-2"
    )
except anthropic.APIError as e:
    logging.error("An error occurred while calling the Anthropic API: %s", e)

This will output log messages with the DEBUG level, including any errors or exceptions that occur.

3. Customize logging configuration: You can further customize the logging configuration, such as logging to a file or using a different log format, by modifying the `logging.basicConfig()` call.

4. Handle specific exception types: The Anthropic Python SDK defines several specific exception types that you can catch and handle, such as `anthropic.APIConnectionError` and `anthropic.APIStatusError`. Catching these exceptions can help you provide more meaningful error messages or implement appropriate fallback behavior.

By following these steps, you can effectively configure error logging for the Anthropic API in your Python application, which can be helpful for troubleshooting and debugging issues.