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8afccec87a
## Why Python callers need control over response history loading and a way to override the service tier for one turn. These options also need runtime compatibility checks to prevent older CLIs from silently ignoring them. ## What changed - Add `include_turns` to sync and async thread resume/fork methods. Omission preserves server defaults; `False` skips response history loading without changing model context. - Add `turn_service_tier` and `source` to sync and async `run()` and `turn()`, and generate both methods together to keep their options aligned. - Require CLI `0.151.0` or newer when sending the new options, with lazy schema checks for unversioned local builds. - Pin the bundled runtime dependency to `0.153.4` and reject unsupported runtime versions during SDK packaging. ## Testing Add coverage for option forwarding, history flag omission and inversion, runtime version checks, cached schema probing, and packaging compatibility. Extend app-server and installed SDK smoke tests to exercise the new options. GitOrigin-RevId: 4bcc9cff687b0651e67852e7c080df7fadac6d76
140 lines
5.4 KiB
Markdown
140 lines
5.4 KiB
Markdown
# FAQ
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## Is the Python SDK stable?
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`openai-codex` publishes stable releases. Install the latest one with
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`pip install openai-codex`.
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## Why does the SDK install a runtime package?
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Stable CLI releases publish the SDK with the same version and an exact runtime
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pin. CLI prereleases do not trigger Python package publishing. Independent SDK
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beta releases can still be published manually with a different version number,
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but must pin a compatible runtime. The dependency is installed automatically.
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See [Python SDK releases](../RELEASING.md) for publishing and retry instructions.
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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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- `Thread.run(...)` starts a turn and returns `TurnResult`.
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- `TurnHandle.run()` / `AsyncTurnHandle.run()` consumes events for an existing turn handle and returns the same `TurnResult` shape.
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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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## Does `include_turns=False` remove the conversation's context?
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No. On `thread_resume(...)` and `thread_fork(...)`, it only skips loading turn
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history into the server's response. Omitting it preserves the server's
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existing default. Retrieve saved history with `thread.read(include_turns=True)`.
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## How do I change the service tier for just one turn?
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Pass `turn_service_tier=` to `thread.run(...)` or `thread.turn(...)`.
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`None` inherits the thread setting, and `"default"` selects standard speed.
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The override applies only when starting a new turn. Use `service_tier=` when
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you want to change the thread's setting for subsequent turns too.
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`source=` on those methods only labels what initiated the turn. It does not
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schedule work or grant authority, and it is ignored when joining an active turn.
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## How do I log in?
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- `login_api_key(...)` authenticates immediately with an API key.
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- `login_chatgpt()` starts browser login and returns a handle with `auth_url`.
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- `login_chatgpt_device_code()` starts device-code login and returns a handle
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with `verification_url` and `user_code`.
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- Interactive handles expose `wait()` for the matching
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`account/login/completed` notification and `cancel()` to stop that attempt.
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- `account()` reads the current account state, and `logout()` clears it.
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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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## How do I choose sandbox access?
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Use the same `sandbox=` keyword for threads and turns:
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```python
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from openai_codex import Sandbox
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thread = codex.thread_start(sandbox=Sandbox.workspace_write)
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result = thread.run("Review only.", sandbox=Sandbox.read_only)
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```
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The presets are:
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- `Sandbox.read_only`: read files without allowing writes.
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- `Sandbox.workspace_write`: the normal default for projects with a recorded trust decision; read files and write inside the workspace and configured writable roots.
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- `Sandbox.full_access`: run without filesystem access restrictions.
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When `sandbox=` is omitted, Codex uses its configured default. A turn
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sandbox override applies to that turn and subsequent turns.
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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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- installation is incomplete and the pinned `openai-codex-cli-bin` dependency is missing
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- local `codex_bin` override points to a missing file
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- a custom local Codex executable does not support the SDK operation being used
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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
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`MethodNotFoundError`, fix the input or use the runtime pinned by the SDK.
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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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- Reading `Turn.items` from live start/completed payloads instead of using `TurnResult.items`.
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- Mixing SDK input classes with raw dicts incorrectly.
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