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## Why The Python SDK previously protected the stdio transport with a single active turn-consumer guard. That avoided competing reads from stdout, but it also meant one `Codex`/`AsyncCodex` client could not stream multiple active turns at the same time. Notifications could also arrive before the caller received a `TurnHandle` and registered for streaming, so the SDK needed an explicit routing layer instead of letting individual API calls read directly from the shared transport. ## What Changed - Added a private `MessageRouter` that owns per-request response queues, per-turn notification queues, pending turn-notification replay, and global notification delivery behind a single stdout reader thread. - Generated typed notification routing metadata so turn IDs come from known payload shapes instead of router-side attribute guessing, with explicit fallback handling for unknown notification payloads. - Updated sync and async turn streaming so `TurnHandle.stream()`/`run()` and `stream_text()` consume only notifications for their own turn ID, while `AsyncAppServerClient` no longer serializes all transport calls behind one async lock. - Cleared pending turn-notification buffers when unregistered turns complete so never-consumed turn handles do not leave stale queues behind. - Removed the internal stream-until helper now that turn completion waiting can register directly with routed turn notifications. - Updated Python SDK docs and focused tests for concurrent transport calls, interleaved turn routing, buffered early notifications, unknown notification routing, async delegation, and routed turn completion behavior. ## Validation - `uv run --extra dev ruff format scripts/update_sdk_artifacts.py src/codex_app_server/_message_router.py src/codex_app_server/client.py src/codex_app_server/generated/notification_registry.py tests/test_client_rpc_methods.py tests/test_public_api_runtime_behavior.py tests/test_async_client_behavior.py` - `uv run --extra dev ruff check scripts/update_sdk_artifacts.py src/codex_app_server/_message_router.py src/codex_app_server/client.py src/codex_app_server/generated/notification_registry.py tests/test_client_rpc_methods.py tests/test_public_api_runtime_behavior.py tests/test_async_client_behavior.py` - `uv run --extra dev pytest tests/test_client_rpc_methods.py tests/test_public_api_runtime_behavior.py tests/test_async_client_behavior.py` - `git diff --check` --------- Co-authored-by: Codex <noreply@openai.com>
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Getting Started
This is the fastest path from install to a multi-turn thread using the public SDK surface.
The SDK is experimental. Treat the API, bundled runtime strategy, and packaging details as unstable until the first public release.
1) Install
From repo root:
cd sdk/python
uv sync
source .venv/bin/activate
Requirements:
- Python
>=3.10 - uv
- installed
openai-codex-cli-binruntime package, or an explicitcodex_binoverride - local Codex auth/session configured
2) Run your first turn (sync)
from codex_app_server import Codex
with Codex() as codex:
server = codex.metadata.serverInfo
print("Server:", None if server is None else server.name, None if server is None else server.version)
thread = codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
result = thread.run("Say hello in one sentence.")
print("Thread:", thread.id)
print("Text:", result.final_response)
print("Items:", len(result.items))
What happened:
Codex()started and initializedcodex app-server.thread_start(...)created a thread.thread.run("...")started a turn, consumed events until completion, and returned the final assistant response plus collected items and usage.result.final_responseisNonewhen no final-answer or phase-less assistant message item completes for the turn.- use
thread.turn(...)when you need aTurnHandlefor streaming, steering, interrupting, or turn IDs/status - one client can consume multiple active turns concurrently; turn streams are routed by turn ID
3) Continue the same thread (multi-turn)
from codex_app_server import Codex
with Codex() as codex:
thread = codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
first = thread.run("Summarize Rust ownership in 2 bullets.")
second = thread.run("Now explain it to a Python developer.")
print("first:", first.final_response)
print("second:", second.final_response)
4) Async parity
Use async with AsyncCodex() as the normal async entrypoint. AsyncCodex
initializes lazily, and context entry makes startup/shutdown explicit.
import asyncio
from codex_app_server import AsyncCodex
async def main() -> None:
async with AsyncCodex() as codex:
thread = await codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
result = await thread.run("Continue where we left off.")
print(result.final_response)
asyncio.run(main())
5) Resume an existing thread
from codex_app_server import Codex
THREAD_ID = "thr_123" # replace with a real id
with Codex() as codex:
thread = codex.thread_resume(THREAD_ID)
result = thread.run("Continue where we left off.")
print(result.final_response)
6) Generated models
The convenience wrappers live at the package root, but the canonical app-server models live under:
from codex_app_server.generated.v2_all import Turn, TurnStatus, ThreadReadResponse
7) Next stops
- API surface and signatures:
docs/api-reference.md - Common decisions/pitfalls:
docs/faq.md - End-to-end runnable examples:
examples/README.md