What this error means

websocket_base_url.replace() replaces ALL occurrences of http:// in URL, corrupting proxy configs: https://proxy.com/forward?target=http://backend → wss://proxy.com/forward?target=ws://backend is a OpenAI API failure pattern reported for developers trying to developer using openai python sdk with a reverse-proxy base url encounters websocket connection failure because the sdk incorrectly replaces all 'http://' substrings instead of only the scheme prefix.. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Issue openai/openai-python #3294 (opened May 21, 2026). Minimal reproducible example provided, exact code snippet showing the bug. Clear suggested fix included. Affects production proxy setups connecting through intermediaries. Category maps to OpenAI API per skill rules.

Common causes

  • Issue openai/openai-python #3294 (opened May 21, 2026). Minimal reproducible example provided, exact code snippet showing the bug. Clear suggested fix included. Affects production proxy setups connecting through intermediaries. Category maps to OpenAI API per skill rules.

Quick fixes

  1. Confirm the exact error signature matches websocket_base_url.replace() replaces ALL occurrences of http:// in URL, corrupting proxy configs: https://proxy.com/forward?target=http://backend → wss://proxy.com/forward?target=ws://backend.
  2. Check the OpenAI API 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.