LiteLLM Mid-Stream Fallback Breaks for Claude Sonnet 4.6/Opus 4.7 (Assistant Prefill Not Supported)

What this error means

litellm.BadRequestError: AnthropicException - This model does not support assistant message prefill is a LiteLLM failure pattern reported for developers trying to fix litellm mid-stream fallback assistant prefill error claude. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

When streaming request fails mid-stream, Router.stream_with_fallbacks appends assistant message with prefix=True. Claude Sonnet 4.6/Opus 4.7 reject this with 400. Fallback feature silently unusable for these models. No documented workaround except monkey-patching.

Common causes

• Users relying on LiteLLM’s streaming fallback feature for Claude models find it silently broken — fallback requests include unsupported assistant prefill, causing 400 errors and hiding the original failure
• When streaming request fails mid-stream, Router.stream_with_fallbacks appends assistant message with prefix=True. Claude Sonnet 4.6/Opus 4.7 reject this with 400. Fallback feature silently unusable for these models. No documented workaround except monkey-patching.

Quick fixes

1. Confirm the exact error signature matches litellm.BadRequestError: AnthropicException - This model does not support assistant message prefill.
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.

Sources checked

• https://github.com/BerriAI/litellm/issues/27967

Evidence note: When streaming request fails mid-stream, Router.stream_with_fallbacks appends assistant message with prefix=True. Claude Sonnet 4.6/Opus 4.7 reject this with 400. Fallback feature silently unusable for these models. No documented workaround except monkey-patching.

Related errors

• LiteLLM streaming fallback
• Claude assistant prefill error
• LiteLLM Router fallback configuration

FAQ

What should I check first?

Start with the exact litellm.BadRequestError: AnthropicException - This model does not support assistant message prefill text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed LiteLLM workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without litellm.BadRequestError: AnthropicException - This model does not support assistant message prefill.