mirror of
https://github.com/pchuan98/codex.git
synced 2026-07-01 00:31:56 +08:00
Owen Lin
703793c22e
## Description This makes Codex Apps tool reads use a shared in-memory snapshot instead of rereading the disk cache every time `list_all_tools()` runs. Disk still seeds the cache on startup and gets updated after successful fetches, but it is no longer the live read path. The core change is that `McpManager` now owns a process-scoped `CodexAppsToolsCache`. Codex threads in the same app-server process now share this Codex Apps in-memory tools snapshot. The snapshot is keyed by the Codex home plus the Codex Apps identity: the active Codex auth user/workspace and the effective Codex Apps MCP source config. There's already code to hard-refresh the cache, so we respect it in this PR. ## Local benchmark I ran a local steady-state microbenchmark of the exact repeated Codex Apps cached-tools read this PR removes, using the same real local cache payload in both trees: `3,678,138` bytes and `381` tools. The cache file was already warm in the OS page cache, so this measures same-process reread/deserialization work rather than cold-disk latency or full turn latency. Each run is 25 iterations (mimicking a turn that makes 25 inference calls). | Version | Run 1 | Run 2 | Avg | |---|---:|---:|---:| | `origin/main` disk read + JSON deserialize + `filter_tools` | `50.755 ms` | `52.894 ms` | `51.825 ms` | | This branch in-memory `current_tools` + `filter_tools` | `0.740 ms` | `0.778 ms` | `0.759 ms` | That removes about `51 ms` from each repeated Codex Apps cached-tools read on this machine, roughly `68x` faster for that subpath. It is useful evidence for the hot path this PR changes, but not a claim that every production turn gets `51 ms` faster; end-to-end impact also depends on the rest of `list_all_tools()` and tool-payload construction. This is on my M2 Max macbook, so with a slower disk this would be much worse (and indeed we did see this really blew up turn runtime with a slow disk).
703793c22e
·
2026-06-25 20:54:48 +00:00
7,854 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.