BerriAI/litellm · error · LassoGuardrailAPIError

Lasso API rate limit exceeded

Error message

Lasso API rate limit exceeded

What it means

Raised as LassoGuardrailAPIError when the Lasso API responds with HTTP 429: your organization has exceeded its Lasso rate limit. The guardrail cannot evaluate the request, so litellm fails the call instead of skipping moderation.

Source

Thrown at litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py:616

        verbose_proxy_logger.error(
            "Error calling Lasso API: %s",
            error,
            extra={
                "guardrail_name": getattr(self, "guardrail_name", "unknown"),
                "message_type": message_type,
                "error_type": type(error).__name__,
            },
        )

        # Handle specific error types if httpx is available
        if HTTPX_AVAILABLE:
            if isinstance(error, httpx.TimeoutException):
                raise LassoGuardrailAPIError("Lasso API timeout")
            elif isinstance(error, httpx.HTTPStatusError):
                if error.response.status_code == 401:
                    raise LassoGuardrailMissingSecrets("Invalid API key")
                elif error.response.status_code == 429:
                    raise LassoGuardrailAPIError("Lasso API rate limit exceeded")
                else:
                    raise LassoGuardrailAPIError(f"API error: {error.response.status_code}")

        # Generic error handling
        raise LassoGuardrailAPIError(f"Failed to verify request safety with Lasso API: {error}")

    def _log_masking_applied(
        self,
        message_type: Literal["PROMPT", "COMPLETION"],
        response: dict[str, Any],
    ) -> None:
        """Log masking application with structured context."""
        conversation_id: Final = getattr(self, "conversation_id", "unknown")
        verbose_proxy_logger.debug(
            "Lasso masking applied",
            extra={
                "guardrail_name": getattr(self, "guardrail_name", "unknown"),
                "message_type": message_type,

View on GitHub (pinned to 77b7c6c40c)

Solutions

1. Retry with exponential backoff and jitter, honoring the Retry-After header if Lasso sends one.
2. Reduce guardrail evaluation pressure: narrow the guardrail to the hooks/modes you actually need (e.g. only pre_call) and avoid guarding low-risk traffic.
3. Check your Lasso plan's rate limits and request a limit increase if sustained traffic legitimately exceeds them.
4. Distribute traffic across multiple Lasso keys/workspaces if your plan supports it.

Example fix

# before
resp = await client.post(lasso_url, headers=headers, json=payload)

# after — honor 429 with backoff (tenacity)
from tenacity import retry, stop_after_attempt, wait_exponential_jitter

@retry(stop=stop_after_attempt(5), wait=wait_exponential_jitter(1, 30),
       retry=retry_if_exception=lambda e: getattr(e, "response", None) is not None and e.response.status_code == 429)
async def call_lasso():
    return await client.post(lasso_url, headers=headers, json=payload)

from litellm.proxy.guardrails.guardrail_hooks.lasso.lasso import LassoGuardrailAPIError

def is_lasso_rate_limit(err: Exception) -> bool:
    """True when the wrapped error is a 429 from Lasso — safe to back off and retry."""
    return isinstance(err, LassoGuardrailAPIError) and "rate limit" in str(err).lower()

import asyncio
from litellm.proxy.guardrails.guardrail_hooks.lasso.lasso import LassoGuardrailAPIError

async def call_with_backoff(hook, data, attempts: int = 5):
    for i in range(attempts):
        try:
            return await hook(data)
        except LassoGuardrailAPIError as e:
            if "rate limit" not in str(e).lower() or i == attempts - 1:
                raise
            await asyncio.sleep(min(2 ** i + 1, 30))  # exponential backoff + jitter

When it happens

Trigger: A guardrail hook sends a request to the Lasso API and the response status is 429 (httpx raises HTTPStatusError with response.status_code == 429), which _handle_api_error re-raises as 'Lasso API rate limit exceeded'.

Common situations: High RPS through the proxy with every call guarded; burst traffic (batch jobs, load tests); a Lasso plan with lower limits than production traffic; multiple litellm instances or environments sharing one Lasso key.

Related errors

• litellm.RateLimitError: {custom_llm_provider}Exception - {er
• Lasso API timeout
• Invalid API key
• API error: {error.response.status_code}
• Failed to verify request safety with Lasso API: {error}

AI-assisted analysis of BerriAI/litellm@77b7c6c40c (2026-08-18). Data as JSON: /api/errors/0cdebef7a8c6dfa2. Report an issue: GitHub.