mirror of
https://github.com/openai/codex.git
synced 2026-05-01 03:42:05 +03:00
0769ed5b5d
Normalize validated initialize metadata back onto InitializeResponse so successful metadata access exposes populated serverInfo fields even when they were derived from userAgent. Also make async lifecycle guidance explicit in the public surface by documenting async with AsyncCodex() as the preferred entrypoint and aligning the AsyncCodex metadata error message with that model. Co-authored-by: Codex <noreply@openai.com>
109 lines
3.2 KiB
Markdown
109 lines
3.2 KiB
Markdown
# Getting Started
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This is the fastest path from install to a multi-turn thread using the public SDK surface.
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The SDK is experimental. Treat the API, bundled runtime strategy, and packaging details as unstable until the first public release.
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## 1) Install
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From repo root:
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```bash
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cd sdk/python
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python -m pip install -e .
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```
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Requirements:
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- Python `>=3.10`
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- installed `codex-cli-bin` runtime package, or an explicit `codex_bin` override
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- local Codex auth/session configured
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## 2) Run your first turn (sync)
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```python
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from codex_app_server import Codex, TextInput
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with Codex() as codex:
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server = codex.metadata.serverInfo
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print("Server:", None if server is None else server.name, None if server is None else server.version)
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thread = codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
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completed_turn = thread.turn(TextInput("Say hello in one sentence.")).run()
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print("Thread:", thread.id)
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print("Turn:", completed_turn.id)
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print("Status:", completed_turn.status)
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print("Items:", len(completed_turn.items or []))
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```
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What happened:
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- `Codex()` started and initialized `codex app-server`.
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- `thread_start(...)` created a thread.
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- `turn(...).run()` consumed events until `turn/completed` and returned the canonical generated app-server `Turn` model.
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- one client can have only one active `TurnHandle.stream()` / `TurnHandle.run()` consumer at a time in the current experimental build
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## 3) Continue the same thread (multi-turn)
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```python
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from codex_app_server import Codex, TextInput
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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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first = thread.turn(TextInput("Summarize Rust ownership in 2 bullets.")).run()
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second = thread.turn(TextInput("Now explain it to a Python developer.")).run()
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print("first:", first.id, first.status)
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print("second:", second.id, second.status)
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```
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## 4) Async parity
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Use `async with AsyncCodex()` as the normal async entrypoint. `AsyncCodex`
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initializes lazily, and context entry makes startup/shutdown explicit.
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```python
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import asyncio
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from codex_app_server import AsyncCodex, TextInput
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async def main() -> None:
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async with AsyncCodex() as codex:
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thread = await codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
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turn = await thread.turn(TextInput("Continue where we left off."))
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completed_turn = await turn.run()
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print(completed_turn.id, completed_turn.status)
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asyncio.run(main())
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```
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## 5) Resume an existing thread
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```python
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from codex_app_server import Codex, TextInput
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THREAD_ID = "thr_123" # replace with a real id
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with Codex() as codex:
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thread = codex.thread_resume(THREAD_ID)
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completed_turn = thread.turn(TextInput("Continue where we left off.")).run()
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print(completed_turn.id, completed_turn.status)
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```
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## 6) Generated models
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The convenience wrappers live at the package root, but the canonical app-server models live under:
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```python
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from codex_app_server.generated.v2_all import Turn, TurnStatus, ThreadReadResponse
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```
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## 7) Next stops
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- API surface and signatures: `docs/api-reference.md`
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- Common decisions/pitfalls: `docs/faq.md`
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- End-to-end runnable examples: `examples/README.md`
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