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## TL;DR Add `thread.run(...)` / `async thread.run(...)` convenience methods to the Python SDK for the common case. - add `RunInput = Input | str` and `RunResult` with `final_response`, collected `items`, and optional `usage` - keep `thread.turn(...)` strict and lower-level for streaming, steering, interrupting, and raw generated `Turn` access - update Python SDK docs, quickstart examples, and tests for the sync and async convenience flows ## Validation - `python3 -m pytest sdk/python/tests/test_public_api_signatures.py sdk/python/tests/test_public_api_runtime_behavior.py` - `python3 -m pytest sdk/python/tests/test_real_app_server_integration.py -k 'thread_run_convenience or async_thread_run_convenience'` (skipped in this environment) --------- 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
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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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result = thread.run("Say hello in one sentence.")
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print("Thread:", thread.id)
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print("Text:", result.final_response)
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print("Items:", len(result.items))
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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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- `thread.run("...")` started a turn, consumed events until completion, and returned the final assistant response plus collected items and usage.
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- `result.final_response` is `None` when no final-answer or phase-less assistant message item completes for the turn.
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- use `thread.turn(...)` when you need a `TurnHandle` for streaming, steering, interrupting, or turn IDs/status
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- one client can have only one active turn consumer (`thread.run(...)`, `TurnHandle.stream()`, or `TurnHandle.run()`) 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
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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.run("Summarize Rust ownership in 2 bullets.")
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second = thread.run("Now explain it to a Python developer.")
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print("first:", first.final_response)
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print("second:", second.final_response)
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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
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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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result = await thread.run("Continue where we left off.")
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print(result.final_response)
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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
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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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result = thread.run("Continue where we left off.")
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print(result.final_response)
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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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