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## Why The Python SDK depends on the app-server runtime package for the bundled `codex` binary and schema source of truth. That relationship should be explicit in package metadata instead of inferred from matching version numbers, so installers, lockfiles, and reviewers can see exactly which runtime the SDK expects. ## What - Declare `openai-codex-cli-bin==0.131.0a4` as a Python SDK dependency. - Update runtime setup helpers to resolve the runtime version from the declared dependency pin. - Refresh the SDK lockfile for the pinned runtime wheel. - Update package/runtime tests and docs that describe where the runtime version comes from. ## Stack 1. This PR `[1/8]` Pin Python SDK runtime dependency 2. #21893 `[2/8]` Generate Python SDK types from pinned runtime 3. #21895 `[3/8]` Run Python SDK tests in CI 4. #21896 `[4/8]` Define Python SDK public API surface 5. #21905 `[5/8]` Rename Python SDK package to `openai-codex` 6. #21910 `[6/8]` Add high-level Python SDK approval mode 7. #22014 `[7/8]` Add Python SDK app-server integration harness 8. #22021 `[8/8]` Add Python SDK Ruff formatting ## Verification - Added coverage for the SDK runtime dependency pin and runtime distribution naming. --------- Co-authored-by: Codex <noreply@openai.com>
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Python SDK Examples
Each example folder contains runnable versions:
sync.py(public sync surface:Codex)async.py(public async surface:AsyncCodex)
All examples intentionally use only public SDK exports from codex_app_server.
Prerequisites
- Python
>=3.10 - Install SDK dependencies for the same Python interpreter you will use to run examples
Recommended setup (from sdk/python):
uv sync
source .venv/bin/activate
When running examples from this repo checkout, the SDK source uses the local
tree and does not bundle a runtime binary. The helper in examples/_bootstrap.py
uses the installed openai-codex-cli-bin runtime package.
If the pinned openai-codex-cli-bin runtime is not already installed, the bootstrap
will download the matching GitHub release artifact, stage a temporary local
openai-codex-cli-bin package, install it into your active interpreter, and clean up
the temporary files afterward.
The pinned runtime version comes from the SDK package dependency.
Run examples
From sdk/python:
python examples/<example-folder>/sync.py
python examples/<example-folder>/async.py
The examples bootstrap local imports from sdk/python/src automatically, so no
SDK wheel install is required. You only need the Python dependencies for your
active interpreter and an installed openai-codex-cli-bin runtime package (either
already present or automatically provisioned by the bootstrap).
Recommended first run
python examples/01_quickstart_constructor/sync.py
python examples/01_quickstart_constructor/async.py
Index
01_quickstart_constructor/- first run / sanity check
02_turn_run/- inspect full turn output fields
03_turn_stream_events/- stream a turn with a small curated event view
04_models_and_metadata/- discover visible models for the connected runtime
05_existing_thread/- resume a real existing thread (created in-script)
06_thread_lifecycle_and_controls/- thread lifecycle + control calls
07_image_and_text/- remote image URL + text multimodal turn
08_local_image_and_text/- local image + text multimodal turn using a generated temporary sample image
09_async_parity/- parity-style sync flow (see async parity in other examples)
10_error_handling_and_retry/- overload retry pattern + typed error handling structure
11_cli_mini_app/- interactive chat loop
12_turn_params_kitchen_sink/- structured output with a curated advanced
turn(...)configuration
- structured output with a curated advanced
13_model_select_and_turn_params/- list models, pick highest model + highest supported reasoning effort, run turns, print message and usage
14_turn_controls/- separate best-effort
steer()andinterrupt()demos with concise summaries
- separate best-effort