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## Why With deferred executors, an environment can become ready between two sampling requests in the same turn. The model-visible environment update, advertised tools, and eventual tool execution must all describe the same request-time view. Otherwise, a request built while only environment B is ready can advertise a tool without an `environment_id`; if higher-priority environment A becomes ready before execution, that call could silently run in A instead. This PR is stacked on #29527. ## Design `run_turn` captures one `Arc<StepContext>` at each sampling-request boundary. That step owns the request's `TurnContext` and environment snapshot. - World-state environment updates and tool planning borrow that same step. - `ToolCallRuntime` retains the `Arc` while asynchronous tool calls execute. - `ToolInvocation` carries the step to handlers; its temporary `turn` compatibility field is derived from the same object. - `ToolRouter` does not retain `StepContext`; it only uses it while constructing the request's tool set. - With `DeferredExecutor` disabled, step capture keeps using the environments frozen at turn start. Simply: every sampling request gets one consistent picture of its environments, from what the model sees through where its tool calls run. ## What changed - Build environment-dependent tool specs from the current request's `StepContext`. - Use that same step for unified exec, legacy shell, `apply_patch`, `view_image`, and `request_permissions` execution. - Hide environment-backed tools, including `request_permissions`, while no environment is attached. - Resolve legacy shell paths and metadata from the selected step environment instead of the stale turn-start environment. - Capture explicit steps at non-turn-loop boundaries such as compaction, prompt debug, and startup prewarm. - Reconcile prompt-debug history from the same step used to build its tools. ## Follow-up - Bind yielded code-mode cells to the tool runtime that created them, so nested calls made after yielding continue to use the originating request's `StepContext`. ## Test plan - `just test -p codex-core deferred_executor_updates_context_and_tools_after_startup` - `just test -p codex-core environment_count_controls_environment_backed_tools` - `just test -p codex-core build_prompt_input_includes_context_and_user_message`
4cc6a4bab5
·
2026-06-23 20:21:13 +00:00
7,749 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.