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## Why The Python SDK can already create threads and run turns, but authentication still has to be arranged outside the SDK. App-server already exposes account login, account inspection, logout, and `account/login/completed` notifications, so SDK users currently have to work around a missing public client layer for a core setup step. This change makes authentication a normal SDK workflow while preserving the backend flow shape: API-key login completes immediately, and interactive ChatGPT flows return live handles that complete later through app-server notifications. ## What changed - Added public sync and async auth methods on `Codex` / `AsyncCodex`: - `login_api_key(...)` - `login_chatgpt()` - `login_chatgpt_device_code()` - `account(...)` - `logout()` - Added public browser-login and device-code handle types with attempt-local `wait()` and `cancel()` helpers. Cancellation stays on the handle instead of a root-level SDK method. - Extended the Python app-server client and notification router so login completion events are routed by `login_id` without consuming unrelated global notifications. - Kept login request/handle logic in a focused internal `_login.py` module so `api.py` remains the public facade instead of absorbing more auth plumbing. - Exported the new handle types plus curated account/login response types from the SDK surfaces. - Updated SDK docs, added sync/async login walkthrough examples, and added a notebook login walkthrough cell. ## Verification Added SDK coverage for: - API-key login, account readback, and logout through the app-server harness in both sync and async clients. - Browser login cancellation plus `handle.wait()` completion through the real app-server boundary used by the Python SDK harness. - Waiter routing that stays scoped across replaced interactive login attempts, plus async handle cancellation coverage. - Login notification demuxing, replay of early completion events, and async client delegation. - Public export/signature assertions. - Real integration-suite smoke coverage for the new examples and notebook login cell.
90 lines
3.3 KiB
Markdown
90 lines
3.3 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 public app-server `Turn` model from `openai_codex.types`.
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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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## 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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- `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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- incompatible/old app-server
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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 public `Turn` model.
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- Mixing SDK input classes with raw dicts incorrectly.
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