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This is PR 2 of the Python SDK PyPI publishing split. [PR 1](https://github.com/openai/codex/pull/18862) refreshed the generated SDK bindings; this PR makes the runtime package itself publishable, and PR 3 will wire the SDK package/version pinning to this runtime package. ## Summary - Rename the runtime distribution to `openai-codex-cli-bin` while keeping the import package as `codex_cli_bin`. - Make the runtime package wheel-only and build `py3-none-<platform>` wheels instead of interpreter-specific wheels. - Add `stage-runtime --codex-version` and `--platform-tag` so release staging can produce the platform wheel matrix from Codex release tags. - Add focused artifact workflow tests for version normalization, platform tag injection, and runtime wheel metadata. ## Why Rename There is already an unofficial PyPI package, [`codex-bin`](https://pypi.org/project/codex-bin/), distributing OpenAI Codex binaries. Publishing the official SDK runtime dependency as `openai-codex-cli-bin` makes the ownership clear, avoids confusing the SDK-pinned runtime wheel with that unowned wrapper, and keeps the import package unchanged as `codex_cli_bin`. ## Tests - `uv run --extra dev pytest tests/test_artifact_workflow_and_binaries.py` -> 21 passed - `uv run --extra dev python scripts/update_sdk_artifacts.py stage-runtime /tmp/codex-python-pr2-rebased/runtime-stage /tmp/codex-python-pr2-rebased/codex --codex-version rust-v0.116.0-alpha.1 --platform-tag macosx_11_0_arm64` - `uv run --with build --extra dev python -m build --wheel /tmp/codex-python-pr2-rebased/runtime-stage` - `uv run --with twine --extra dev twine check /tmp/codex-python-pr2-rebased/runtime-stage/dist/openai_codex_cli_bin-0.116.0a1-py3-none-macosx_11_0_arm64.whl` ## Note - Full `uv run --extra dev pytest` currently fails because regenerating from schemas already on `main` adds new DeviceKey Python types. I left that generated catch-up out of this runtime-only PR.
99 lines
3.4 KiB
Markdown
99 lines
3.4 KiB
Markdown
# FAQ
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## Thread vs turn
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- A `Thread` is conversation state.
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- A `Turn` is one model execution inside that thread.
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- Multi-turn chat means multiple turns on the same `Thread`.
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## `run()` vs `stream()`
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- `TurnHandle.run()` / `AsyncTurnHandle.run()` is the easiest path. It consumes events until completion and returns the canonical generated app-server `Turn` model.
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- `TurnHandle.stream()` / `AsyncTurnHandle.stream()` yields raw notifications (`Notification`) so you can react event-by-event.
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Choose `run()` for most apps. Choose `stream()` for progress UIs, custom timeout logic, or custom parsing.
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## Sync vs async clients
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- `Codex` is the sync public API.
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- `AsyncCodex` is an async replica of the same public API shape.
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- Prefer `async with AsyncCodex()` for async code. It is the standard path for
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explicit startup/shutdown, and `AsyncCodex` initializes lazily on context
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entry or first awaited API use.
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If your app is not already async, stay with `Codex`.
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## Public kwargs are snake_case
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Public API keyword names are snake_case. The SDK still maps them to wire camelCase under the hood.
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If you are migrating older code, update these names:
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- `approvalPolicy` -> `approval_policy`
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- `baseInstructions` -> `base_instructions`
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- `developerInstructions` -> `developer_instructions`
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- `modelProvider` -> `model_provider`
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- `modelProviders` -> `model_providers`
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- `sortKey` -> `sort_key`
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- `sourceKinds` -> `source_kinds`
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- `outputSchema` -> `output_schema`
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- `sandboxPolicy` -> `sandbox_policy`
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## Why only `thread_start(...)` and `thread_resume(...)`?
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The public API keeps only explicit lifecycle calls:
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- `thread_start(...)` to create new threads
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- `thread_resume(thread_id, ...)` to continue existing threads
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This avoids duplicate ways to do the same operation and keeps behavior explicit.
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## Why does constructor fail?
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`Codex()` is eager: it starts transport and calls `initialize` in `__init__`.
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Common causes:
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- published runtime package (`openai-codex-cli-bin`) is not installed
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- local `codex_bin` override points to a missing file
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- local auth/session is missing
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- incompatible/old app-server
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Maintainers stage releases by building the SDK once and the runtime once per
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platform with the same pinned runtime version. Publish `openai-codex-cli-bin` as
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platform wheels only; do not publish an sdist:
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```bash
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cd sdk/python
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python scripts/update_sdk_artifacts.py generate-types
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python scripts/update_sdk_artifacts.py \
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stage-sdk \
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/tmp/codex-python-release/codex-app-server-sdk \
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--runtime-version 1.2.3
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python scripts/update_sdk_artifacts.py \
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stage-runtime \
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/tmp/codex-python-release/openai-codex-cli-bin \
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/path/to/codex \
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--runtime-version 1.2.3
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```
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## Why does a turn "hang"?
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A turn is complete only when `turn/completed` arrives for that turn ID.
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- `run()` waits for this automatically.
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- With `stream()`, keep consuming notifications until completion.
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## How do I retry safely?
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Use `retry_on_overload(...)` for transient overload failures (`ServerBusyError`).
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Do not blindly retry all errors. For `InvalidParamsError` or `MethodNotFoundError`, fix inputs/version compatibility instead.
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## Common pitfalls
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- Starting a new thread for every prompt when you wanted continuity.
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- Forgetting to `close()` (or not using context managers).
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- Assuming `run()` returns extra SDK-only fields instead of the generated `Turn` model.
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- Mixing SDK input classes with raw dicts incorrectly.
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