LiteLLM / LiteLLM
LiteLLM Responses API Drops cache_control on Input Text Blocks, Breaks Prompt Caching
fix LiteLLM cache_control dropped / Responses API input_text cache_control not working Includes evidence for LiteLLM troubleshooting demand.
- Category
- LiteLLM
- Error signature
Responses API drops cache_control on input_text content blocks (inconsistent with tool cache_control)- Quick fix
- Compare the failing environment with a known working setup, then change one configuration value at a time.
- Updated
What this error means
Responses API drops cache_control on input_text content blocks (inconsistent with tool cache_control) is a LiteLLM failure pattern reported for developers trying to fix litellm cache_control dropped / responses api input_text cache_control not working. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Reported 2026-05-14: cache_control on input_text silently dropped in Responses API conversion. Inconsistent behavior between content block types.
Common causes
- When using OpenAI Responses API endpoint with cache_control on input_text content blocks, the cache_control field is silently dropped during conversion. This breaks prompt caching for developers using the Responses API through LiteLLM.
- Reported 2026-05-14: cache_control on input_text silently dropped in Responses API conversion. Inconsistent behavior between content block types.
Quick fixes
- Confirm the exact error signature matches
Responses API drops cache_control on input_text content blocks (inconsistent with tool cache_control). - 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: Reported 2026-05-14: cache_control on input_text silently dropped in Responses API conversion. Inconsistent behavior between content block types.
Related errors
- LiteLLM cache_control not working
- OpenAI Responses API caching issues
FAQ
What should I check first?
Start with the exact Responses API drops cache_control on input_text content blocks (inconsistent with tool cache_control) 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 Responses API drops cache_control on input_text content blocks (inconsistent with tool cache_control).