What this error means

RouterRateLimitError: No Retry-After header returned when all deployments in cooldown period is a LiteLLM failure pattern reported for developers trying to add retry-after header support to litellm rate limit errors so clients can implement proper exponential backoff. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue BerriAI/litellm#27823 by b4lduin (May 13 2026). When LiteLLM proxy router exhausts all deployed endpoints, it raises RouterRateLimitError but provides no Retry-After header. Clients have no way to know when to retry, causing immediate hammering of cooldown deployments. Affects self-hosted LiteLLM proxy deployments managing multiple model providers. Labels: llm translation, high commercial impact for proxy operators who need predictable rate limiting behavior.

Common causes

  • GitHub issue BerriAI/litellm#27823 by b4lduin (May 13 2026). When LiteLLM proxy router exhausts all deployed endpoints, it raises RouterRateLimitError but provides no Retry-After header. Clients have no way to know when to retry, causing immediate hammering of cooldown deployments. Affects self-hosted LiteLLM proxy deployments managing multiple model providers. Labels: llm translation, high commercial impact for proxy operators who need predictable rate limiting behavior.

Quick fixes

  1. Confirm the exact error signature matches RouterRateLimitError: No Retry-After header returned when all deployments in cooldown period.
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.