LiteLLM / LiteLLM
LiteLLM proxy buffers Anthropic streamed responses instead of sending deltas incrementally
Production LiteLLM proxy user expects incremental streaming for Anthropic model calls but receives all content in a single buffered batch — breaks real-time chat UX Includes evidence for LiteLLM troubleshooting demand.
- Category
- LiteLLM
- Error signature
Proxied Anthropic Response is Buffered: response is sent in one large batch despite stream=true setting; works correctly for OpenAI models under same config- Quick fix
- Compare the failing environment with a known working setup, then change one configuration value at a time.
- Updated
What this error means
Proxied Anthropic Response is Buffered: response is sent in one large batch despite stream=true setting; works correctly for OpenAI models under same config is a LiteLLM failure pattern reported for developers trying to production litellm proxy user expects incremental streaming for anthropic model calls but receives all content in a single buffered batch — breaks real-time chat ux. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub Issue #28384 on BerriAI/litellm opened May 20, 2026 (13 hours ago) by dogmd. The bug is Anthropic-specific — OpenAI proxied calls stream fine with identical settings. User confirmed no nginx buffering (proxy_buffering off). Involves LiteLLM v1.85.0 running on Kubernetes with PostgreSQL DB. High urgency: broken streaming is critical for any production chat application using Anthropic models through LiteLLM proxy.
Common causes
- GitHub Issue #28384 on BerriAI/litellm opened May 20, 2026 (13 hours ago) by dogmd. The bug is Anthropic-specific — OpenAI proxied calls stream fine with identical settings. User confirmed no nginx buffering (proxy_buffering off). Involves LiteLLM v1.85.0 running on Kubernetes with PostgreSQL DB. High urgency: broken streaming is critical for any production chat application using Anthropic models through LiteLLM proxy.
Quick fixes
- Confirm the exact error signature matches
Proxied Anthropic Response is Buffered: response is sent in one large batch despite stream=true setting; works correctly for OpenAI models under same config. - 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: GitHub Issue #28384 on BerriAI/litellm opened May 20, 2026 (13 hours ago) by dogmd. The bug is Anthropic-specific — OpenAI proxied calls stream fine with identical settings. User confirmed no nginx buffering (proxy_buffering off). Involves LiteLLM v1.85.0 running on Kubernetes with PostgreSQL DB. High urgency: broken streaming is critical for any production chat application using Anthropic models through LiteLLM proxy.
Related errors
- LiteLLM
FAQ
What should I check first?
Start with the exact Proxied Anthropic Response is Buffered: response is sent in one large batch despite stream=true setting; works correctly for OpenAI models under same config 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 Proxied Anthropic Response is Buffered: response is sent in one large batch despite stream=true setting; works correctly for OpenAI models under same config.