What this error means

oauth handler overwrites anthropic-beta header — only oauth-2025-04-20 retained, newer beta features dropped (e.g. prompt caching) is a LiteLLM failure pattern reported for developers trying to requests with newer anthropic beta headers silently lose functionality when proxied through litellm's oauth handler; developers unaware of silent feature loss. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue #22398 on BerriAI/litellm — optionally_handle_anthropic_oauth() replaces entire anthropic-beta header, stripping client-sent beta features. Silent bug affecting paid LiteLLM proxy deployments. Distinct from general rate-limit/error issues. Category: LiteLLM (proxy-specific).

Common causes

  • GitHub issue #22398 on BerriAI/litellm — optionally_handle_anthropic_oauth() replaces entire anthropic-beta header, stripping client-sent beta features. Silent bug affecting paid LiteLLM proxy deployments. Distinct from general rate-limit/error issues. Category: LiteLLM (proxy-specific).

Quick fixes

  1. Confirm the exact error signature matches oauth handler overwrites anthropic-beta header — only oauth-2025-04-20 retained, newer beta features dropped (e.g. prompt caching).
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. Verify the account session, API key, provider settings, and environment where the failing tool is running.

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.