LiteLLM / LiteLLM
LiteLLM strips reasoning_content from DeepSeek V4 Pro responses, breaking multi-turn conversations
Fix LiteLLM breaking DeepSeek V4 Pro multi-turn conversations by stripping reasoning_content Includes evidence for LiteLLM troubleshooting demand.
- Category
- LiteLLM
- Error signature
LiteLLM BadRequestError: reasoning_content must be passed back to the API (DeepSeek V4 Pro multi-turn)- Quick fix
- Compare the failing environment with a known working setup, then change one configuration value at a time.
- Updated
What this error means
LiteLLM BadRequestError: reasoning_content must be passed back to the API (DeepSeek V4 Pro multi-turn) is a LiteLLM failure pattern reported for developers trying to fix litellm breaking deepseek v4 pro multi-turn conversations by stripping reasoning_content. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
17 reactions. First turn succeeds, all subsequent turns fail with 400. Root cause: Message.init in litellm/types/utils.py deletes reasoning_content when None. Old R1 behavior (strip) conflicts with V4 Pro requirement (preserve).
Common causes
- DeepSeek V4 Pro requires reasoning_content to be passed back in multi-turn conversations, but LiteLLM strips it during serialization (carried over from R1 behavior)
- 17 reactions. First turn succeeds, all subsequent turns fail with 400. Root cause: Message.init in litellm/types/utils.py deletes reasoning_content when None. Old R1 behavior (strip) conflicts with V4 Pro requirement (preserve).
Quick fixes
- Confirm the exact error signature matches
LiteLLM BadRequestError: reasoning_content must be passed back to the API (DeepSeek V4 Pro multi-turn). - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- 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
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- 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
Evidence note: 17 reactions. First turn succeeds, all subsequent turns fail with 400. Root cause: Message.init in litellm/types/utils.py deletes reasoning_content when None. Old R1 behavior (strip) conflicts with V4 Pro requirement (preserve).
Related errors
- Ollama deepseek-v4-pro:cloud HTTP 500
- LiteLLM Structured Output fails on Bedrock
FAQ
What should I check first?
Start with the exact LiteLLM BadRequestError: reasoning_content must be passed back to the API (DeepSeek V4 Pro multi-turn) 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: reasoning_content must be passed back to the API (DeepSeek V4 Pro multi-turn).