Files
codex/sdk/python/docs/api-reference.md
Ahmed Ibrahim f0166cadbb [codex] Return TurnResult from Python turn handles (#23151)
## Why

`TurnHandle.run()` returned the raw app-server `Turn`, whose live
start/completed payloads do not include loaded `items`, so users saw
empty `items` after starting a turn. That made the handle-based path
behave differently from `Thread.run(...)`, and pushed examples toward
persisted-thread reads plus helper extraction.

This PR makes the run APIs standalone: starting a turn and running it
returns collected turn data directly, or fails visibly when required
stream events are missing.

## What Changed

- Replaces the public `RunResult` export with `TurnResult`.
- Adds turn metadata to `TurnResult`: `id`, `status`, `error`,
`started_at`, `completed_at`, and `duration_ms`, alongside
`final_response`, `items`, and `usage`.
- Changes `TurnHandle.run()` and `AsyncTurnHandle.run()` to consume
stream events with the same collector used by `Thread.run(...)`.
- Exports `TurnError` from `openai_codex.types` for the new result
shape.
- Updates tests, examples, docs, and the walkthrough notebook to use
`result.final_response` and `result.items` directly.
- Removes persisted-thread helper paths and placeholder/skipped control
flows from the public examples and notebook.

## Verification

- `python3 -m py_compile ...` over changed SDK, example, and test Python
files.
- `python3 -c "import json;
json.load(open('sdk/python/notebooks/sdk_walkthrough.ipynb'))"`
- `git diff --check`
- `PYTHONPATH=sdk/python/src python3 -c ...` import/signature smoke for
`TurnResult`, `TurnHandle.run`, and `AsyncTurnHandle.run`.
2026-05-17 06:17:22 -07:00

266 lines
8.9 KiB
Markdown

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