mirror of
https://github.com/openai/codex.git
synced 2026-05-20 11:12:43 +00:00
## Summary
- Allow thread.turn and turn.steer, including async variants, to accept
RunInput so plain strings work alongside typed input objects.
- Export RunInput and update the SDK artifact generator so regenerated
turn methods keep the same signature and normalization.
- Update docs, examples, notebook cells, and tests to use string
shorthand for text-only turns while keeping typed inputs for multimodal
input.
## Validation
- uv run --extra dev ruff format .
- uv run --extra dev ruff check --output-format=github .
- python3 -m py_compile sdk/python/src/openai_codex/__init__.py
sdk/python/src/openai_codex/api.py
sdk/python/src/openai_codex/_inputs.py
sdk/python/scripts/update_sdk_artifacts.py
sdk/python/tests/test_public_api_signatures.py
sdk/python/tests/test_app_server_streaming.py
sdk/python/tests/test_app_server_turn_controls.py
sdk/python/tests/test_real_app_server_integration.py
- python3 -c "import json;
json.load(open('sdk/python/notebooks/sdk_walkthrough.ipynb'))"
- sdk/python/.venv/bin/python -c "import inspect, openai_codex; from
openai_codex import Thread, AsyncThread, TurnHandle, AsyncTurnHandle,
RunInput; funcs=[Thread.run, Thread.turn, AsyncThread.run,
AsyncThread.turn, TurnHandle.steer, AsyncTurnHandle.steer]; assert
all(inspect.signature(fn).parameters['input'].annotation == 'RunInput'
for fn in funcs); assert RunInput is openai_codex.RunInput"
271 lines
9.0 KiB
Markdown
271 lines
9.0 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 starts default to `ApprovalMode.auto_review`; turn starts accept an optional `approval_mode` override.
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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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Thread,
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AsyncThread,
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TurnHandle,
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AsyncTurnHandle,
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TurnResult,
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Input,
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InputItem,
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RunInput,
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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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TurnError,
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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=None, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=None, summary=None) -> TurnResult`
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- `turn(input: str | Input, *, approval_mode=None, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=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=None, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=None, summary=None) -> Awaitable[TurnResult]`
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- `turn(input: str | Input, *, approval_mode=None, cwd=None, effort=None, model=None, output_schema=None, personality=None, sandbox_policy=None, service_tier=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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- `id: str`
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- `status: TurnStatus`
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- `error: TurnError | None`
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- `started_at: int | None`
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- `completed_at: int | None`
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- `duration_ms: int | None`
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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()`) before collecting the turn result.
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## TurnHandle / AsyncTurnHandle
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### TurnHandle
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- `steer(input: str | Input) -> TurnSteerResponse`
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- `interrupt() -> TurnInterruptResponse`
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- `stream() -> Iterator[Notification]`
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- `run() -> TurnResult`
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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: str | Input) -> Awaitable[TurnSteerResponse]`
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- `interrupt() -> Awaitable[TurnInterruptResponse]`
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- `stream() -> AsyncIterator[Notification]`
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- `run() -> Awaitable[TurnResult]`
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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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RunInput = Input | str
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```
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Use a plain `str` as shorthand for `TextInput(...)` anywhere a turn input is accepted:
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`thread.run("...")`, `thread.turn("...")`, and `turn.steer("...")`.
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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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