mirror of
https://github.com/pchuan98/codex.git
synced 2026-07-01 00:31:56 +08:00
Ahmed Ibrahim
46946bb91c
## Summary - Treat `sdk/python` as a development template with source version `0.0.0-dev`, matching the existing Python runtime packaging pattern. - Have `python-v*` tags supply the published SDK beta version through the existing `stage-sdk --sdk-version` path. - Remove the workflow check requiring a source version bump for each beta release and remove its now-unused host Python setup step. - Keep the reviewed runtime dependency pin at `openai-codex-cli-bin==0.132.0`. - Remove beta-number-specific documentation so it does not need editing for each publish. ## Why The package staging script already writes the release version into the artifact. Requiring the checked-in SDK template version to match every tag adds release-only source churn without changing the package users receive. ## Validation - Not run locally; relying on online CI for this workflow and metadata change. ## Release After this PR lands, publish the next beta by pushing tag `python-v0.1.0b2` from merged `main`.
123 lines
4.5 KiB
Markdown
123 lines
4.5 KiB
Markdown
# FAQ
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## Is the Python SDK stable?
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`openai-codex` is a public beta. Install it with
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`pip install openai-codex`; public APIs may change before `1.0`. While beta
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releases are the only published SDK releases, pip selects the latest beta.
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After a stable release exists, pass `--pre` to opt into newer prereleases.
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## Why does the SDK install a runtime package?
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The SDK and runtime packages are versioned independently. Each SDK release
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pins and installs one compatible runtime dependency automatically.
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## Thread vs turn
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- A `Thread` is conversation state.
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- A `Turn` is one model execution inside that thread.
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- Multi-turn chat means multiple turns on the same `Thread`.
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## `run()` vs `stream()`
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- `Thread.run(...)` starts a turn and returns `TurnResult`.
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- `TurnHandle.run()` / `AsyncTurnHandle.run()` consumes events for an existing turn handle and returns the same `TurnResult` shape.
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- `TurnHandle.stream()` / `AsyncTurnHandle.stream()` yields raw notifications (`Notification`) so you can react event-by-event.
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Choose `run()` for most apps. Choose `stream()` for progress UIs, custom timeout logic, or custom parsing.
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## Sync vs async clients
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- `Codex` is the sync public API.
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- `AsyncCodex` is an async replica of the same public API shape.
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- Prefer `async with AsyncCodex()` for async code. It is the standard path for
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explicit startup/shutdown, and `AsyncCodex` initializes lazily on context
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entry or first awaited API use.
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If your app is not already async, stay with `Codex`.
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## How do I log in?
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- `login_api_key(...)` authenticates immediately with an API key.
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- `login_chatgpt()` starts browser login and returns a handle with `auth_url`.
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- `login_chatgpt_device_code()` starts device-code login and returns a handle
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with `verification_url` and `user_code`.
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- Interactive handles expose `wait()` for the matching
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`account/login/completed` notification and `cancel()` to stop that attempt.
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- `account()` reads the current account state, and `logout()` clears it.
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## Public kwargs are snake_case
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Public API keyword names are snake_case. The SDK still maps them to wire camelCase under the hood.
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If you are migrating older code, update these names:
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- `approvalPolicy` -> `approval_policy`
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- `baseInstructions` -> `base_instructions`
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- `developerInstructions` -> `developer_instructions`
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- `modelProvider` -> `model_provider`
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- `modelProviders` -> `model_providers`
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- `sortKey` -> `sort_key`
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- `sourceKinds` -> `source_kinds`
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- `outputSchema` -> `output_schema`
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## How do I choose sandbox access?
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Use the same `sandbox=` keyword for threads and turns:
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```python
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from openai_codex import Sandbox
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thread = codex.thread_start(sandbox=Sandbox.workspace_write)
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result = thread.run("Review only.", sandbox=Sandbox.read_only)
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```
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The presets are:
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- `Sandbox.read_only`: read files without allowing writes.
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- `Sandbox.workspace_write`: the normal default for projects with a recorded trust decision; read files and write inside the workspace and configured writable roots.
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- `Sandbox.full_access`: run without filesystem access restrictions.
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When `sandbox=` is omitted, Codex uses its configured default. A turn
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sandbox override applies to that turn and subsequent turns.
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## Why only `thread_start(...)` and `thread_resume(...)`?
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The public API keeps only explicit lifecycle calls:
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- `thread_start(...)` to create new threads
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- `thread_resume(thread_id, ...)` to continue existing threads
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This avoids duplicate ways to do the same operation and keeps behavior explicit.
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## Why does constructor fail?
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`Codex()` is eager: it starts transport and calls `initialize` in `__init__`.
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Common causes:
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- installation is incomplete and the pinned `openai-codex-cli-bin` dependency is missing
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- local `codex_bin` override points to a missing file
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- a custom local Codex executable does not support the SDK operation being used
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## Why does a turn "hang"?
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A turn is complete only when `turn/completed` arrives for that turn ID.
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- `run()` waits for this automatically.
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- With `stream()`, keep consuming notifications until completion.
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## How do I retry safely?
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Use `retry_on_overload(...)` for transient overload failures (`ServerBusyError`).
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Do not blindly retry all errors. For `InvalidParamsError` or
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`MethodNotFoundError`, fix the input or use the runtime pinned by the SDK.
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## Common pitfalls
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- Starting a new thread for every prompt when you wanted continuity.
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- Forgetting to `close()` (or not using context managers).
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- Reading `Turn.items` from live start/completed payloads instead of using `TurnResult.items`.
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- Mixing SDK input classes with raw dicts incorrectly.
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