LiteLLM TypeError — Streaming Crashes with NoneType When Provider Returns Reasoning Field in Delta

What this error means

TypeError: 'async for' requires an object with __aiter__ method, got NoneType is a LiteLLM failure pattern reported for developers trying to fix litellm crash with typeerror ‘async for requires an object with aiter method’ when streaming from models with reasoning/thinking output. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

When stream=True with providers returning reasoning field in delta (e.g., Scaleway), LiteLLM streaming parser crashes with TypeError because the response object becomes None. Affects any reasoning/thinking model streamed through LiteLLM proxy.

Common causes

• As more providers (Scaleway, Anthropic via proxy) return reasoning/thinking fields in streaming delta, LiteLLM crashes with TypeError. This breaks any application using streamed reasoning output through LiteLLM.
• When stream=True with providers returning reasoning field in delta (e.g., Scaleway), LiteLLM streaming parser crashes with TypeError because the response object becomes None. Affects any reasoning/thinking model streamed through LiteLLM proxy.

Quick fixes

1. Confirm the exact error signature matches TypeError: 'async for' requires an object with __aiter__ method, got NoneType.
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/27670

Evidence note: When stream=True with providers returning reasoning field in delta (e.g., Scaleway), LiteLLM streaming parser crashes with TypeError because the response object becomes None. Affects any reasoning/thinking model streamed through LiteLLM proxy.

Related errors

• LiteLLM streaming reasoning field error
• LiteLLM async streaming NoneType crash
• LiteLLM Chain of Thought streaming broken

FAQ

What should I check first?

Start with the exact TypeError: 'async for' requires an object with __aiter__ method, got NoneType 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 TypeError: 'async for' requires an object with __aiter__ method, got NoneType.