BerriAI/litellm · error · Timeout

AnthropicException Timeout

Error message

AnthropicException Timeout - {error_str}

What it means

Anthropic-specific status mapping: an upstream Anthropic error with HTTP 503 is re-raised as ServiceUnavailableError (timeout-class), signaling Anthropic is temporarily unavailable; the message suggests handling via litellm.ServiceUnavailableError.

Solutions

1. Increase the timeout for Anthropic requests or retry.
2. Reduce request size if the model takes too long to respond.

When it happens

Trigger: Thrown at litellm/litellm_core_utils/exception_mapping_utils.py:599 when the library encounters an invalid state.

Common situations: See trigger scenarios.

Understand the failure class

• Timeouts: ETIMEDOUT, deadlines, and hung requests — what actually expires when a request times out.

AI-assisted analysis of BerriAI/litellm@77b7c6c40c (2026-08-18). Data as JSON: /api/errors/9d1b7e706e1d0fc7. Report an issue: GitHub.

Appendix: source

Thrown at litellm/litellm_core_utils/exception_mapping_utils.py:599

                model=model,
                response=getattr(original_exception, "response", None),
            )
        elif original_exception.status_code == 502:
            raise BadGatewayError(
                message=f"AnthropicException BadGatewayError - {error_str}",
                llm_provider="anthropic",
                model=model,
                response=getattr(original_exception, "response", None),
            )
        elif original_exception.status_code == 503:
            raise litellm.ServiceUnavailableError(
                message=f"AnthropicException - {error_str}. Handle with `litellm.ServiceUnavailableError`.",
                llm_provider="anthropic",
                model=model,
                response=getattr(original_exception, "response", None),
            )
        elif original_exception.status_code == 504:  # gateway timeout error
            raise Timeout(
                message=f"AnthropicException Timeout - {error_str}",
                model=model,
                llm_provider="anthropic",
                exception_status_code=original_exception.status_code,
            )


def _map_replicate_exception(
    *,
    model: str,
    original_exception: _ProviderHTTPException,
    custom_llm_provider: str,
    error_str: str,
    exception_type: str,
    exception_provider: str,
    extra_information: str,
) -> None:
    if "Incorrect authentication token" in error_str:

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