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https://github.com/pchuan98/codex.git
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Zanie Blue
6a9a49b334
## Summary - reuse the history-bearing `StoredThread` loaded while probing for a running thread - avoid rereading and reparsing the rollout when that probe finds no active process - reload after shutting down a loaded thread because shutdown may flush newer rollout items - add a regression test that verifies cold resume performs one history-bearing store read ## Problem `thread/resume` first reads the persisted thread with history while checking whether the thread is already running. When no running process exists, cold resume currently falls through to `resume_thread_from_rollout`, which reads and parses the same history again. That duplicate work grows with rollout size and remains on the synchronous resume path even when the caller requests `excludeTurns`. ## Background The duplicate read was introduced by #24528, which fixed resume overrides for idle cached threads. To support resumes specified by rollout path, `resume_running_thread` began loading the stored thread with history so it could resolve the canonical thread ID and determine whether a cached `CodexThread` was already loaded. That history is needed when the loaded-thread path handles the request. On a cold miss, however, the function's boolean result could only report that no loaded thread handled the request. It discarded the history-bearing `StoredThread`, and the normal cold-resume path immediately loaded and parsed the same rollout again. This change preserves the idle cached-thread behavior from #24528 while allowing the cold-resume path to reuse the probe result. ## Performance I benchmarked real retained rollouts using isolated `CODEX_HOME` directories, explicit rollout paths, debug builds of the commit and its exact parent, and alternating parent/patch order. The table below uses `thread/resume` with `excludeTurns: true`; response payload sizes were identical. | Rollout size | Records | Parent median | Patch median | Median paired saving | | ---: | ---: | ---: | ---: | ---: | | 6 MB | 3,574 | 541 ms | 441 ms | 132 ms | | 30 MB | 15,220 | 1.505 s | 1.041 s | 701 ms | | 60 MB | 31,453 | 2.644 s | 1.742 s | 970 ms | | 149 MB | 100,874 | 10.506 s | 7.156 s | 3.350 s | | 559 MB | 259,734 | 27.759 s | 16.725 s | 9.836 s | The absolute saving increases with thread size, as expected when removing one complete JSONL history read and parse. Total resume time is also content-dependent, so the relationship is not perfectly linear. I also tested full-history resume with `excludeTurns: false`. The response payload was byte-identical between variants, and the same size-dependent improvement remained visible: | Rollout size | Parent median | Patch median | Median paired saving | | ---: | ---: | ---: | ---: | | 6 MB | 1.052 s | 904 ms | 270 ms | | 30 MB | 2.667 s | 1.762 s | 924 ms | | 60 MB | 8.464 s | 6.272 s | 3.680 s | | 149 MB | 26.719 s | 12.118 s | 14.601 s | | 559 MB | 40.359 s | 25.475 s | 16.590 s | ## Validation - `just test -p codex-app-server cold_thread_resume_reuses_non_local_history_probe` - `just fix -p codex-app-server -p codex-thread-store` - `just fmt`
6a9a49b334
·
2026-06-09 11:16:27 -05:00
7,254 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.