LiteLLM Proxied Anthropic Responses Buffered Despite stream=true Setting

What this error means

Anthropic proxied response is buffered: delta JSON lines sent in one large batch despite stream=true configuration is a LiteLLM failure pattern reported for developers trying to fix litellm proxy buffering anthropic sse streams instead of sending real-time deltas, when both openai and anthropic share same proxy config. 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. User runs LiteLLM v1.85.0 in Kubernetes with Anthropic + OpenAI models. Streaming works for OpenAI but Anthropic responses arrive as single batch. Config includes proxy_buffering off in nginx, Redis cache, Prometheus callbacks. Not a network issue — pure LiteLLM proxy behavior difference between providers. High-value P1 tech with 47.9k GitHub stars.

Common causes

• GitHub issue #28384 on BerriAI/litellm opened May 20, 2026. User runs LiteLLM v1.85.0 in Kubernetes with Anthropic + OpenAI models. Streaming works for OpenAI but Anthropic responses arrive as single batch. Config includes proxy_buffering off in nginx, Redis cache, Prometheus callbacks. Not a network issue — pure LiteLLM proxy behavior difference between providers. High-value P1 tech with 47.9k GitHub stars.

Quick fixes

1. Confirm the exact error signature matches Anthropic proxied response is buffered: delta JSON lines sent in one large batch despite stream=true configuration.
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/28384

Evidence note: GitHub issue #28384 on BerriAI/litellm opened May 20, 2026. User runs LiteLLM v1.85.0 in Kubernetes with Anthropic + OpenAI models. Streaming works for OpenAI but Anthropic responses arrive as single batch. Config includes proxy_buffering off in nginx, Redis cache, Prometheus callbacks. Not a network issue — pure LiteLLM proxy behavior difference between providers. High-value P1 tech with 47.9k GitHub stars.

Related errors

• LiteLLM

FAQ

What should I check first?

Start with the exact Anthropic proxied response is buffered: delta JSON lines sent in one large batch despite stream=true configuration 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 Anthropic proxied response is buffered: delta JSON lines sent in one large batch despite stream=true configuration.