Codex CLI requests consistently cut off at ~150s (stream disconnected); please increase or make timeout configurable

Resolved 💬 4 comments Opened Sep 11, 2025 by PoseidonLi0514 Closed Sep 29, 2025

What version of Codex is running?

codex-cli 0.33.0

Which model were you using?

gpt-5

What platform is your computer?

Linux 6.14.0-1011-aws x86_64 x86_64

What steps can reproduce the bug?

Summary:
Codex CLI requests are consistently cut off at around 150 seconds, which makes it difficult to complete complex coding tasks that require longer reasoning and multi-file edits. The stream terminates with the error shown below. The VS Code extension seems to allow a longer timeout and often completes the same tasks, but the exact duration is unclear.

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Steps to Reproduce

  1. Open Codex CLI and start a session with streaming enabled.
  2. Ask Codex to implement a complex, multi-file refactor or generate substantial code with tests (e.g., multi-step agent flow that applies patches and explains changes).
  3. Let the model think and stream for a while without interrupting.
After approximately 150 seconds, the stream stops and the CLI reports an error.

Error message

stream error: stream disconnected before completion: Transport error: error decoding response body

What is the expected behavior?

  • Long-running requests should be allowed to finish streaming if the model is still producing output.
  • The timeout should be longer by default (e.g., 5–10 minutes), or at least configurable via a flag or environment variable.
  • The timeout value should be consistent (or clearly documented) across the CLI and the VS Code extension.

What do you see instead?

  • Requests consistently terminate near 150s with a transport/stream decoding error.
  • Complex tasks (long reasoning, multi-file patches) fail to complete in the CLI.

Additional information

  • Network is stable; this occurs across multiple sessions and prompts.

Impact

  • High: Complex refactors, larger code generation, and longer reasoning sessions regularly fail in CLI usage.
  • This forces users to split work into many smaller prompts or switch tools.

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