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f0166cadbb
## 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`.
140 lines
3.8 KiB
Markdown
140 lines
3.8 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, so the public API and runtime requirements may keep evolving before 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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uv sync
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source .venv/bin/activate
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```
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Requirements:
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- Python `>=3.10`
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- uv
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- installed `openai-codex-cli-bin` runtime package, or an explicit `codex_bin` override
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## 2) Authenticate when needed
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Existing Codex auth state is reused automatically. To authenticate from the SDK,
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use the flow that fits your app:
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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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codex.login_api_key("sk-...")
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account = codex.account()
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print(account.account)
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```
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Interactive ChatGPT browser login returns a handle that carries the URL and the
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matching completion event:
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```python
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with Codex() as codex:
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login = codex.login_chatgpt()
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print(login.auth_url)
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completed = login.wait()
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print(completed.success)
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```
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Device-code login works the same way with
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`login_chatgpt_device_code()`, which exposes `verification_url`, `user_code`,
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and `wait()`.
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## 3) Run your first turn (sync)
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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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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 `TurnResult` with turn metadata, final assistant response, 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, or interrupting before collecting `TurnResult`
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- one client can consume multiple active turns concurrently; turn streams are routed by turn ID
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## 4) Continue the same thread (multi-turn)
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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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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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## 5) 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 openai_codex 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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## 6) Resume an existing thread
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```python
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from openai_codex 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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## 7) Public app-server types
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The convenience wrappers live at the package root. Public app-server value and
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event types live under:
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```python
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from openai_codex.types import ThreadReadResponse, Turn, TurnStatus
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```
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## 8) 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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