## What changed Add a downstream workflow that builds the Python SDK and runtime from the stable CLI release commit, using the CLI version for both packages and the SDK's exact runtime dependency. Publish and verify the runtime on PyPI before publishing the SDK. Require a successful CLI `release` job, an unchanged release tag, and complete runtime assets. Skip CLI prereleases and allow publication despite unrelated publisher failures. Support retries by CLI workflow run ID and accept existing PyPI uploads while verifying the complete release. Document release setup, retry procedures, and independent SDK releases. ## Testing Add resolver unit tests covering tag resolution, prerelease skipping, partial reruns, pagination, invalid runs, moved tags, missing assets, and equivalent automatic and manual release resolution. GitOrigin-RevId: 4ec6b2e77c94c851507dbe7200ea420994fce36e
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FAQ
Is the Python SDK stable?
openai-codex publishes stable releases. Install the latest one with
pip install openai-codex.
Why does the SDK install a runtime package?
Stable CLI releases publish the SDK with the same version and an exact runtime pin. CLI prereleases do not trigger Python package publishing. Independent SDK beta releases can still be published manually with a different version number, but must pin a compatible runtime. The dependency is installed automatically. See Python SDK releases for publishing and retry instructions.
Thread vs turn
- A
Threadis conversation state. - A
Turnis one model execution inside that thread. - Multi-turn chat means multiple turns on the same
Thread.
run() vs stream()
Thread.run(...)starts a turn and returnsTurnResult.TurnHandle.run()/AsyncTurnHandle.run()consumes events for an existing turn handle and returns the sameTurnResultshape.TurnHandle.stream()/AsyncTurnHandle.stream()yields raw notifications (Notification) so you can react event-by-event.
Choose run() for most apps. Choose stream() for progress UIs, custom timeout logic, or custom parsing.
Sync vs async clients
Codexis the sync public API.AsyncCodexis an async replica of the same public API shape.- Prefer
async with AsyncCodex()for async code. It is the standard path for explicit startup/shutdown, andAsyncCodexinitializes lazily on context entry or first awaited API use.
If your app is not already async, stay with Codex.
How do I log in?
login_api_key(...)authenticates immediately with an API key.login_chatgpt()starts browser login and returns a handle withauth_url.login_chatgpt_device_code()starts device-code login and returns a handle withverification_urlanduser_code.- Interactive handles expose
wait()for the matchingaccount/login/completednotification andcancel()to stop that attempt. account()reads the current account state, andlogout()clears it.
Public kwargs are snake_case
Public API keyword names are snake_case. The SDK still maps them to wire camelCase under the hood.
If you are migrating older code, update these names:
approvalPolicy->approval_policybaseInstructions->base_instructionsdeveloperInstructions->developer_instructionsmodelProvider->model_providermodelProviders->model_providerssortKey->sort_keysourceKinds->source_kindsoutputSchema->output_schema
How do I choose sandbox access?
Use the same sandbox= keyword for threads and turns:
from openai_codex import Sandbox
thread = codex.thread_start(sandbox=Sandbox.workspace_write)
result = thread.run("Review only.", sandbox=Sandbox.read_only)
The presets are:
Sandbox.read_only: read files without allowing writes.Sandbox.workspace_write: the normal default for projects with a recorded trust decision; read files and write inside the workspace and configured writable roots.Sandbox.full_access: run without filesystem access restrictions.
When sandbox= is omitted, Codex uses its configured default. A turn
sandbox override applies to that turn and subsequent turns.
Why only thread_start(...) and thread_resume(...)?
The public API keeps only explicit lifecycle calls:
thread_start(...)to create new threadsthread_resume(thread_id, ...)to continue existing threads
This avoids duplicate ways to do the same operation and keeps behavior explicit.
Why does constructor fail?
Codex() is eager: it starts transport and calls initialize in __init__.
Common causes:
- installation is incomplete and the pinned
openai-codex-cli-bindependency is missing - local
codex_binoverride points to a missing file - a custom local Codex executable does not support the SDK operation being used
Why does a turn "hang"?
A turn is complete only when turn/completed arrives for that turn ID.
run()waits for this automatically.- With
stream(), keep consuming notifications until completion.
How do I retry safely?
Use retry_on_overload(...) for transient overload failures (ServerBusyError).
Do not blindly retry all errors. For InvalidParamsError or
MethodNotFoundError, fix the input or use the runtime pinned by the SDK.
Common pitfalls
- Starting a new thread for every prompt when you wanted continuity.
- Forgetting to
close()(or not using context managers). - Reading
Turn.itemsfrom live start/completed payloads instead of usingTurnResult.items. - Mixing SDK input classes with raw dicts incorrectly.