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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.
259 lines
8.8 KiB
Markdown
259 lines
8.8 KiB
Markdown
# OpenAI Codex SDK — API Reference
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Public surface of `openai_codex` for app-server v2.
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This SDK surface is experimental. Turn streams are routed by turn ID so one client can consume multiple active turns concurrently.
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Thread and turn starts expose `approval_mode`. `ApprovalMode.auto_review` is the default; use `ApprovalMode.deny_all` to deny escalated permissions.
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## Package Entry
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```python
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from openai_codex import (
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Codex,
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AsyncCodex,
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ApprovalMode,
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ChatgptLoginHandle,
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DeviceCodeLoginHandle,
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AsyncChatgptLoginHandle,
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AsyncDeviceCodeLoginHandle,
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RunResult,
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Thread,
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AsyncThread,
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TurnHandle,
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AsyncTurnHandle,
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Input,
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InputItem,
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TextInput,
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ImageInput,
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LocalImageInput,
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SkillInput,
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MentionInput,
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)
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from openai_codex.types import (
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Account,
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AccountLoginCompletedNotification,
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CancelLoginAccountResponse,
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CancelLoginAccountStatus,
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GetAccountResponse,
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InitializeResponse,
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ThreadItem,
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ThreadTokenUsage,
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TurnStatus,
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)
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```
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- Version: `openai_codex.__version__`
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- Requires Python >= 3.10
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- Public app-server value and event types live in `openai_codex.types`
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## Codex (sync)
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```python
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Codex(config: AppServerConfig | None = None)
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```
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Properties/methods:
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- `metadata -> InitializeResponse`
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- `close() -> None`
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- `login_api_key(api_key: str) -> None`
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- `login_chatgpt() -> ChatgptLoginHandle`
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- `login_chatgpt_device_code() -> DeviceCodeLoginHandle`
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- `account(*, refresh_token: bool = False) -> GetAccountResponse`
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- `logout() -> None`
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- `thread_start(*, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, ephemeral=None, model=None, model_provider=None, personality=None, sandbox=None) -> Thread`
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- `thread_list(*, archived=None, cursor=None, cwd=None, limit=None, model_providers=None, sort_key=None, source_kinds=None) -> ThreadListResponse`
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- `thread_resume(thread_id: str, *, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, model=None, model_provider=None, personality=None, sandbox=None) -> Thread`
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- `thread_fork(thread_id: str, *, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, model=None, model_provider=None, sandbox=None) -> Thread`
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- `thread_archive(thread_id: str) -> ThreadArchiveResponse`
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- `thread_unarchive(thread_id: str) -> Thread`
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- `models(*, include_hidden: bool = False) -> ModelListResponse`
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Context manager:
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```python
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with Codex() as codex:
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...
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```
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## AsyncCodex (async parity)
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```python
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AsyncCodex(config: AppServerConfig | None = None)
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```
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Preferred usage:
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```python
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async with AsyncCodex() as codex:
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...
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```
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`AsyncCodex` initializes lazily. Context entry is the standard path because it
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ensures startup and shutdown are paired explicitly.
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Properties/methods:
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- `metadata -> InitializeResponse`
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- `close() -> Awaitable[None]`
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- `login_api_key(api_key: str) -> Awaitable[None]`
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- `login_chatgpt() -> Awaitable[AsyncChatgptLoginHandle]`
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- `login_chatgpt_device_code() -> Awaitable[AsyncDeviceCodeLoginHandle]`
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- `account(*, refresh_token: bool = False) -> Awaitable[GetAccountResponse]`
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- `logout() -> Awaitable[None]`
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- `thread_start(*, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, ephemeral=None, model=None, model_provider=None, personality=None, sandbox=None) -> Awaitable[AsyncThread]`
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- `thread_list(*, archived=None, cursor=None, cwd=None, limit=None, model_providers=None, sort_key=None, source_kinds=None) -> Awaitable[ThreadListResponse]`
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- `thread_resume(thread_id: str, *, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, model=None, model_provider=None, personality=None, sandbox=None) -> Awaitable[AsyncThread]`
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- `thread_fork(thread_id: str, *, approval_mode=ApprovalMode.auto_review, base_instructions=None, config=None, cwd=None, developer_instructions=None, ephemeral=None, model=None, model_provider=None, sandbox=None) -> Awaitable[AsyncThread]`
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- `thread_archive(thread_id: str) -> Awaitable[ThreadArchiveResponse]`
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- `thread_unarchive(thread_id: str) -> Awaitable[AsyncThread]`
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- `models(*, include_hidden: bool = False) -> Awaitable[ModelListResponse]`
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Async context manager:
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```python
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async with AsyncCodex() as codex:
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...
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```
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## Login handles
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### ChatgptLoginHandle / AsyncChatgptLoginHandle
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- `login_id: str`
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- `auth_url: str`
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- `wait() -> AccountLoginCompletedNotification`
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- `cancel() -> CancelLoginAccountResponse`
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Async handle methods return awaitables.
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### DeviceCodeLoginHandle / AsyncDeviceCodeLoginHandle
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- `login_id: str`
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- `verification_url: str`
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- `user_code: str`
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- `wait() -> AccountLoginCompletedNotification`
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- `cancel() -> CancelLoginAccountResponse`
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Async handle methods return awaitables.
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`wait()` consumes only the completion notification for its matching login
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attempt. API-key login completes synchronously and does not return a handle.
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## Thread / AsyncThread
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`Thread` and `AsyncThread` share the same shape and intent.
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### Thread
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- `run(input: str | Input, *, approval_mode=ApprovalMode.auto_review, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=None, summary=None) -> RunResult`
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- `turn(input: Input, *, approval_mode=ApprovalMode.auto_review, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, summary=None) -> TurnHandle`
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- `read(*, include_turns: bool = False) -> ThreadReadResponse`
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- `set_name(name: str) -> ThreadSetNameResponse`
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- `compact() -> ThreadCompactStartResponse`
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### AsyncThread
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- `run(input: str | Input, *, approval_mode=ApprovalMode.auto_review, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=None, summary=None) -> Awaitable[RunResult]`
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- `turn(input: Input, *, approval_mode=ApprovalMode.auto_review, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, summary=None) -> Awaitable[AsyncTurnHandle]`
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- `read(*, include_turns: bool = False) -> Awaitable[ThreadReadResponse]`
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- `set_name(name: str) -> Awaitable[ThreadSetNameResponse]`
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- `compact() -> Awaitable[ThreadCompactStartResponse]`
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`run(...)` is the common-case convenience path. It accepts plain strings, starts
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the turn, consumes notifications until completion, and returns a small result
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object with:
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- `final_response: str | None`
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- `items: list[ThreadItem]`
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- `usage: ThreadTokenUsage | None`
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`final_response` is `None` when the turn finishes without a final-answer or
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phase-less assistant message item.
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Use `turn(...)` when you need low-level turn control (`stream()`, `steer()`,
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`interrupt()`) or the public `Turn` model from `TurnHandle.run()`.
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## TurnHandle / AsyncTurnHandle
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### TurnHandle
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- `steer(input: Input) -> TurnSteerResponse`
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- `interrupt() -> TurnInterruptResponse`
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- `stream() -> Iterator[Notification]`
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- `run() -> openai_codex.types.Turn`
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Behavior notes:
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- `stream()` and `run()` consume only notifications for their own turn ID
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- one `Codex` instance can stream multiple active turns concurrently
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### AsyncTurnHandle
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- `steer(input: Input) -> Awaitable[TurnSteerResponse]`
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- `interrupt() -> Awaitable[TurnInterruptResponse]`
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- `stream() -> AsyncIterator[Notification]`
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- `run() -> Awaitable[openai_codex.types.Turn]`
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Behavior notes:
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- `stream()` and `run()` consume only notifications for their own turn ID
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- one `AsyncCodex` instance can stream multiple active turns concurrently
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## Inputs
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```python
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@dataclass class TextInput: text: str
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@dataclass class ImageInput: url: str
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@dataclass class LocalImageInput: path: str
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@dataclass class SkillInput: name: str; path: str
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@dataclass class MentionInput: name: str; path: str
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InputItem = TextInput | ImageInput | LocalImageInput | SkillInput | MentionInput
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Input = list[InputItem] | InputItem
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```
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## Public Types
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The SDK wrappers return and accept public app-server models wherever possible:
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```python
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from openai_codex.types import (
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Account,
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AccountLoginCompletedNotification,
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CancelLoginAccountResponse,
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CancelLoginAccountStatus,
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GetAccountResponse,
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ThreadReadResponse,
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Turn,
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TurnStatus,
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)
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```
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## Retry + errors
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```python
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from openai_codex import (
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retry_on_overload,
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JsonRpcError,
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MethodNotFoundError,
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InvalidParamsError,
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ServerBusyError,
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is_retryable_error,
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)
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```
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- `retry_on_overload(...)` retries transient overload errors with exponential backoff + jitter.
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- `is_retryable_error(exc)` checks if an exception is transient/overload-like.
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## Example
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```python
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from openai_codex import Codex
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with Codex() as codex:
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thread = codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
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result = thread.run("Say hello in one sentence.")
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print(result.final_response)
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```
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