What this error means

stream_timeout not enforced on first chunk; hanging providers cause completions to fail is a LiteLLM failure pattern reported for developers trying to 使用 litellm proxy 的用户发现 stream_timeout 参数在首 chunk 未生效,导致慢启动 provider(如 bedrock)请求被错误终止. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub BerriAI/litellm#19909 (2026-01-27) 确认 stream_timeout 在第一 chunk 不强制执行的问题。还有 #8652 (2025-02-18) 记录 Bedrock 模型的 Stream Timeout 失效。直接命中 P1 LiteLLM 类别,属于代理层计费/路由关键路径上的 bug。mapped to 'LiteLLM' approved category.

Common causes

  • GitHub BerriAI/litellm#19909 (2026-01-27) 确认 stream_timeout 在第一 chunk 不强制执行的问题。还有 #8652 (2025-02-18) 记录 Bedrock 模型的 Stream Timeout 失效。直接命中 P1 LiteLLM 类别,属于代理层计费/路由关键路径上的 bug。mapped to 'LiteLLM' approved category.

Quick fixes

  1. Confirm the exact error signature matches stream_timeout not enforced on first chunk; hanging providers cause completions to fail.
  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.