What this error means

aembedding() missing num_retries kwarg — no failover for embedding model groups is a LiteLLM failure pattern reported for developers trying to fix litellm embedding router not retrying or failing over when embedding host is unreachable. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Bug report (2026-05-07) identifies aembedding() in router.py doesn't set num_retries before calling async completion, causing zero retries and no failover for embedding model groups when a host is unreachable.

Common causes

  • LiteLLM proxy users with multiple embedding deployments expect automatic failover when a host goes down. The aembedding() method skips num_retries, causing single-attempt failures with no fallback — breaking production RAG/embedding pipelines.
  • Bug report (2026-05-07) identifies aembedding() in router.py doesn't set num_retries before calling async completion, causing zero retries and no failover for embedding model groups when a host is unreachable.

Quick fixes

  1. Confirm the exact error signature matches aembedding() missing num_retries kwarg — no failover for embedding model groups.
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

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.